{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 第5章  数据的直观分析及可视化"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 5.1 特殊统计图的绘制"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "#基本设置\n",
    "import numpy as np                             #加载numpy包\n",
    "np.set_printoptions(precision=4)               #设置numpy输出为4位有效数"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5.1.1 函数图"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "（1）初等函数图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0.    ,  0.213 ,  0.426 ,  0.639 ,  0.852 ,  1.0649,  1.2779,\n",
       "        1.4909,  1.7039,  1.9169,  2.1299,  2.3429,  2.5559,  2.7689,\n",
       "        2.9819,  3.1948,  3.4078,  3.6208,  3.8338,  4.0468,  4.2598,\n",
       "        4.4728,  4.6858,  4.8988,  5.1117,  5.3247,  5.5377,  5.7507,\n",
       "        5.9637,  6.1767,  6.3897,  6.6027,  6.8157,  7.0286,  7.2416,\n",
       "        7.4546,  7.6676,  7.8806,  8.0936,  8.3066,  8.5196,  8.7326,\n",
       "        8.9456,  9.1585,  9.3715,  9.5845,  9.7975, 10.0105, 10.2235,\n",
       "       10.4365, 10.6495, 10.8625, 11.0754, 11.2884, 11.5014, 11.7144,\n",
       "       11.9274, 12.1404, 12.3534, 12.5664])"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from math import pi                 #调用math中的圆周率参数\n",
    "x=np.linspace(0,4*pi,60);x          #生成[0,4*pi]上30个等差数列"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from numpy import sin,cos,log,exp   #调用numpy中的初等函数\n",
    "import matplotlib.pyplot as plt     #加载matplotlib包的绘图函数\n",
    "plt.plot(x,sin(x));                 #正弦函数 y=sin(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(x,cos(x));                 #余弦函数 y=cos(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(x,log(x+1));               #对数函数 y=log(x+1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(x,exp(x));                 #指数函数 y=exp(x)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "（2）椭圆函数图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "t=np.linspace(0,2*pi);\n",
    "x=2*sin(t);y=3*cos(t);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(x,y,c='red'); \n",
    "plt.axvline(x=0); plt.axhline(y=0);\n",
    "plt.text(0.2,1,r'$\\frac{x^2}{a^2}+\\frac{y^2}{b^2}=1$',fontsize=15);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 5.1.2 气泡图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x=np.linspace(-4,4,20); \n",
    "y=x**2;                         # y=x^2 抛物线\n",
    "plt.scatter(x,y);               #二维散点图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXAAAAD4CAYAAAD1jb0+AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8/fFQqAAAACXBIWXMAAAsTAAALEwEAmpwYAAAcdUlEQVR4nO3deZRcZb3u8e+vph4zpzMPHUiIkDAXQoCgIpwTEUVFFJUACsQJj5zjuiw9rIvXo3cdPHqdlopGwKAg6lEQxAlEMB4IkU4ImAkMCZ10TEiTOd3prul3/+gKJp10d3VXde3a7fNZK4vUrp3aDz08vfutd+/X3B0REQmfSNABRERkYFTgIiIhpQIXEQkpFbiISEipwEVEQipWzoONHTvWGxsby3lIEZHQW7Fixavu3tB9e1kLvLGxkaampnIeUkQk9Mys+VjbNYQiIhJSKnARkZAq6xBKf7g7f960i8V/2sizzXvI5HJMHFnDdefP4G2nTKImEQ06oohIj7btPcgPlzXzwLNbOdCRobYqyttOmcQ15zYydXRtSY5h5byUPplMeiFj4O2pDNff3cSqLXs4mMpyeMLaRJSqWIR7rz+HkyYNH7ywIiIDdM/TzXz+4bU4kMrkXtsejxoRM266aBYffePMgl/PzFa4e7L79oobQsnlnA8teYYVzbtp71beAO2pLLvb07x38TI272wPJKOISE/uX9nCF361ls5M7ojyBkhnnc5Mjm88toElT24q+lh9FriZ3WVmO8xsdbftnzCz9Wa2xsz+q+gkeX/8ayvPt+yls9v/eHdtnRm+9Lv1pTqsiEjRUpkcn31oDR3p3vvrYDrLF3/7Au2pTFHHK+QMfAmw4PANZvYm4DLgVHefA3y5qBSH+e4fX6I9le1zv5zDI2tfYU97qlSHFhEpyiNrt5PLFTYsbQa/eHZrUcfrs8DdfSmwq9vmjwK3uXtnfp8dRaU4zMrNewreNxGL8FzL3lIdWkSkKEtfbKWtgBNQ6BoOfnx9a1HHG+gY+AnAfDNbbmZ/NLOzetrRzBaZWZOZNbW29h02m+3fm6rdx5hERILS19DJUftnCiv7ngy0wGPAaOAc4H8BPzUzO9aO7r7Y3ZPunmxoOOpK0KOMqksUHCKbcyaOqC54fxGRwTR9TC3x6DGr8CjRiDF9THHTCQda4C3A/d7lz0AOGFtUkrwPnD2NqlhhscbUJZijqYQiUiGuOHMqkWOfyx4lETXe//rpRR1voAX+C+BNAGZ2ApAAXi0qSd4HzplGNNL3B6AmHuUTF86khxN/EZGymzamlrMaR/d5Fh6LGCeMH1b0tSyFTCO8D1gGzDazFjO7DrgLOC4/tfDHwDVeoiuCxg2r5lsfOIPqeM/RauJRLj1lIlckp5bikCIiJfPN95/OxBE1PZZ4LGKMqU/wvauPui6n3yrySkyAlZt384WH17Lmb/uIRYycQyQCtfEYn7hwJgvnTdfZt4hUpH0daf7z1+t54NkWYpEI2ZwTjRjpbI63njyRW956ImPqqwp+vZ6uxKzYAj9k06ttPLdlD6lsjqmjajl7xmgiBQyxiIgEra0zw5/++ip7D6YYVh3n/FljGV4d7/fr9FTgFXszq0NmjK1jxti6oGOIiPRbXVWMBXMnDNrrV9y9UEREpDAqcBGRkFKBi4iElApcRCSkVOAiIiGlAhcRCSkVuIhISKnARURCSgUuIhJSKnARkZBSgYuIhJQKXEQkpFTgIiIhpQIXEQmpQlbkucvMduRX3+n+3KfMzM2sJOthiohI4Qo5A18CLOi+0cymAv8EbC5xJhERKUCfBe7uS4Fdx3jqq8DNQPmW9BERkdcMaAzczC4Dtrr7cwXsu8jMmsysqbW1dSCHExGRY+h3gZtZLfDvwK2F7O/ui9096e7JhoaG/h5ORER6MJAz8OOBGcBzZvYyMAVYaWaDt/CbiIgcpd+LGrv7X4Bxhx7nSzzp7q+WMJeIiPShkGmE9wHLgNlm1mJm1w1+LBER6UufZ+Du/r4+nm8sWRoRESmYrsQUEQkpFbiISEipwEVEQqrfs1DCpHV/Jz9avplH120nnXFOmFDPh86bwWlTR2JmQccTkQqWyuT43Zrt/Gj5Zl490Mno+gTvf/00FsydQFUsGnQ8AMy9fFfCJ5NJb2pqKsuxftq0hVt/sRoHOjM5ACIGVbEoZzWOYvHVSarjlfFJEJHKsmHHAd7/vadp68zQlsq+tr0uEaUmEeVHN5zDCeOHlS2Pma1w92T37UNyCOWRNdu59cHVdGRyr5U3QM7hYDrL8k27+Mg9KwJMKCKV6tUDnVzxnado3d95RHkDtKWy7DyQ4orvLGPHvo6AEv7dkCtwd+c/Hl5LRzrX4z6dmRzLN+5i9da9ZUwmImGw5MmXaevM9HiXPgfaUxnu/J9N5Yx1TEOuwFdt2cOutlSf+6UyOb7/ZPCfABGpLD98uplUtveh5XTWuXf5ZnK5YG/GOuQKvHlnO4W8PZl1Z8OOA4OeR0TCoyOdZX9HuqB9OzNZ2lKZQU7UuyFX4FWxCIVOMEnEhtz/vogUIR6NFLzAQTbngXfIkGuw188YTbqPX38AauJR3nryxDIkEpGwiEaM06aMLGjfOZOGBz6dcMgV+Jj6Ki583Tji0b5Pw9915pQyJBKRMPnoG4+nNtF7MdcmonzkDTPLlKhnQ67AAb7wjrmMra/qscSr4xG++t7TGF4dL3MyEal0F580ngVzJ1DTw3UiNfEoF75uHJecHPwSCEOywMfUV/Grf5nPW+ZOpCoWob4qRn1VjJp4lNkThnHXNWexYG7wH3wRqTxmxv+74lRuumgWI2vjr/VHfVWMETVxbrxwJt+48vSKuJp7yF6Jecie9hQrmneTzuaYMbae2RPKd/WUiIRbJpujqXk3u9pSjKpNcFbjKGLR8p/39nQl5pC+FwrAyNoEbz5xfNAxRCSEYtEI5xw3JugYPSpkRZ67zGyHma0+bNuXzGy9mT1vZg+Y2chBTSkiIkcp5HeBJcCCbtseBea6+ynAi8BnSpxLRET60GeBu/tSYFe3bY+4+6FLkJ6ma2V6EREpo1KMxn8I+E1PT5rZIjNrMrOm1tbWEhxORESgyAI3s1uADHBvT/u4+2J3T7p7sqGhoZjDiYjIYQY8C8XMrgUuBd7s5ZyLKCIiwAAL3MwWADcDb3D39tJGEhGRQhQyjfA+YBkw28xazOw64JvAMOBRM1tlZt8Z5JwiItJNn2fg7v6+Y2y+cxCyiIhIPwzJe6GIiPwjUIGLiISUClxEJKRU4CIiIaUCFxEJKRW4iEhIqcBFREJKBS4iElIqcBGRkFKBi4iElApcRCSkVOAiIiGlAhcRCSkVeAGyOSeVyQUdQ0QGwN3pSGcZiuvODHhFnn8Ef960i6///kWWbdwJwNj6Kq6fP4Or5zVSHY8GnE5EerN1z0G++YcNPLCyhVQ2RyIW4fIzpvDxN81k0siaoOOVhPX1U8nM7qJr6bQd7j43v2008BOgEXgZeI+77+7rYMlk0puamoqMXB4/eWYzn31oDR3pI8+8q+MRZo8fxk8+PE8lLlKhXnxlP5ff/hTtqQzZw76FYxGjNhHl/o+dy8xxw4IL2E9mtsLdk923FzKEsgRY0G3bp4HH3H0W8Fj+8ZDRsrudWx88urwBOtI51m/fz9d+/9cAkolIX9ydG37QxIGOI8sbIJNz9ndkWPSDFUNiSKXPAnf3pcCubpsvA+7O//1u4B2ljRWsHy5rJtfLJ7czk+Oep5s1Li5SgZqad9O6v5OevoMd2L6vg2e37CljqsEx0Dcxx7v7tvzftwPjS5SnIjz10k7S2d5/Oufcadmt9ZxFKs2qzXtIdz/17iaTdVZt3lOeQIOo6Fko3vV7SI9tZ2aLzKzJzJpaW1uLPVxZRCPW5z7uEItoEo9IpYlEDLPev4fNCvs+r3QDbaBXzGwiQP6/O3ra0d0Xu3vS3ZMNDQ0DPFx5/fOc8VTHe//Q1FfFmDJqaLyTLTKUnD9zLH11swHnzRxbljyDaaAF/hBwTf7v1wAPliZOZbjyrGlEevkJXhOP8pE3HEdkCPwEFxlqZk8YxokThxPr4fszFjFOnjKCmePqy5ys9PoscDO7D1gGzDazFjO7DrgNuNjM/gpclH88ZIyqS3DH1UlqE1Hi0SO/CGoTUS4+aTwfPG9GQOlEpC+LFyaZMKKamm5TfWviUSaNrOH2q84MKFlp9TkPvJTCNA8cui4EWPLkJh5+fhudmRyzJwzjwxccxxtOaOhzjE1EgtWeynD/yhaWPNXMrgMpxtQnuPa8Rt55+mRqE+G6hrGneeAqcBGRClfMhTwiIlKBVOAiIiGlAhcRCSkVuIhISKnARURCSgUuIhJSKnARkZBSgYuIhJQKXEQkpFTgIiIhpQIXEQkpFbiISEipwEVEQkoFLiISUipwEZGQKqrAzexfzWyNma02s/vMrLpUwUREpHcDLnAzmwz8C5B097lAFLiyVMFERKR3xQ6hxIAaM4sBtcDfio8kIiKFGHCBu/tW4MvAZmAbsNfdH+m+n5ktMrMmM2tqbW0deFIRETlCMUMoo4DLgBnAJKDOzK7qvp+7L3b3pLsnGxoaBp5URESOUMzSzBcBm9y9FcDM7gfOBe4pRbChIJtznnhhB//d1MLejjTnzBjN+86exrhheq9XpBCrt+7lh8uaad7VxvEN9Vw9r5HZE4YFHatiFFPgm4FzzKwWOAi8GdCS83kd6SxX3bGctdv20Z7KArCyeTffXbqRO65Ocu7MsQEnFKlst/1mHUueepl0xsm688ymXfx8ZQs3vmkmN144K+h4FaGYMfDlwM+AlcBf8q+1uES5Qu+236znL1v3vlbeAJ2ZHO2pLNf/oIn9HekA04lUtj+sf4W7n2qmI50j6w5A1qEjneNbj7/E8o07A05YGYqaheLun3X317n7XHdf6O6dpQoWZh3pLD95Zgudmdwxn3d3fvHs1jKnEgmPbz/+EgfT2WM+15HO8t0/bixzosqkKzEHwY59nZj1/PzBdI7VW/eVL5BIyGzYcaDH5xxYv13fP6ACHxTDa2Jkst7j87GIMaY+UcZEIuEyvCbe6/Mja3t//h+FCnwQjKxNcOb0UfR0Eh6LGJefOaWsmUTC5ANnT6M6fux6qolHWTivsbyBKpQKfJB8/h1zqKuKEenW4jXxKO87exrHN9QHE0wkBBbOm86UUbUkYkdWVFUswvHj6njn6ZMDSlZZVOCDZOa4YfzyE+ezYM4EYhHDDKaOquE/LpvDrZeeFHQ8kYpWm4jxwMfO5ep506mrihIxGF4d47rzZ/DfHz6X6ng06IgVwdx7HqsttWQy6U1N/3hTxXM5J5Pzo84mRKRv7k4qmyMRjWC9zQ4Ywsxshbsnu28v5kIeKVAkYiS6j6WISEHMjKqYzriPRaeEIiIhpQIXEQkpFbiISEipwEVEQkoFLiISUipwEZGQUoGLiISUClxEJKRU4CIiIVVUgZvZSDP7mZmtN7N1ZjavVMFERKR3xV5K/3Xgt+7+bjNLALUlyCQiIgUYcIGb2QjgAuBaAHdPAanSxBIRkb4UM4QyA2gFvm9mz5rZHWZW130nM1tkZk1m1tTa2lrE4URE5HDFFHgMOAO43d1PB9qAT3ffyd0Xu3vS3ZMNDQ1FHE5ERA5XTIG3AC3uvjz/+Gd0FbqIiJTBgAvc3bcDW8xsdn7Tm4G1JUklIiJ9KnYWyieAe/MzUDYCHyw+khzi7jzxQit3P/UyO9tSXHDCWK49dwYNw6qCjiZSkNVb9/K9P23kpdYDzJk0ghvmH8fMcVoPtlS0pFoF+9wv1/DjZ7ZwMJUFIBGLUJuI8tDHz2faGM3YlMr20Kqt3Pzz50llcuQcogaJWJTFV5/J/Fl6P6w/elpSTVdiVqgXtu/nvj9vfq28AVKZHPsOpvncL9cEmEykbx3pLJ++/y90pLvKGyDrcDCd5d9++hy5XPlOHIcyFXiF+t2a7aQzuaO25xyeeLGVcv7mJNJfyzftItLDAsTtnRnWbd9X5kRDkwq8QuVyTk8V7e6ov6WS5Xr7AjX09VsiKvAKdfGc8cdcidsM5s8aS0Sr3EsFO3vGaLI9DJNUxaKcOHF4mRMNTSrwCjVn0gjedupEahN/L/FYxKivinHr2+YEmEykb7WJGP/n7SdRE//712/EoDoe4YuXn0JUJyAlUew0QhlEX7z8FObPauDup15mV1uK+Sc08OELjmPSyJqgo4n06b1nTeO4hnpuf+IlNr3axokTh/OxNx7P3Mkjgo42ZGgaoYhIhdM0QhGRIUYFLiISUipwEZGQUoGLiISUClxEJKRU4CIiIaUCFxEJKRW4iEhIqcBFREKq6AI3s2h+VfqHSxFIREQKU4oz8E8C60rwOiIi0g9FFbiZTQHeCtxRmjgiIlKoYs/AvwbcDBy9dEyemS0ysyYza2ptbS3ycCIicsiAC9zMLgV2uPuK3vZz98XunnT3ZEODFjINQuv+Tl58ZT+ZbI8/Z0V6tK8jzfrt+45Yn1UqQzH3Az8PeLuZXQJUA8PN7B53v6o00aRYnZks//rjVfx+/Q7iESMWjfD1K0/jjbPHBR1NQsDd+eJv1/P9J18mFjVyOfj0W17HNec2Bh1N8gZ8Bu7un3H3Ke7eCFwJ/EHlXVm+8siLPLZ+B6lMjrZUlr0H03z0nhXsPNAZdDQJgV8+v427n2qmM5OjrTPLwXSW236znmc37w46muRpHvgQ9rOVLXQetbK98ejaVwLJI+Hyo+WbOZg+ctikI5PlZytaAkok3ZVkSTV3fwJ4ohSvJaVzzFUHrWthZJG+HOvrxHrYLsHQGfgQ9p7kVKpj3T7FDhefNCGYQBIqV509/YhFiaFrRfkrzpwaUCLpTgU+hN100Qn889wJJGIRahNRRtcluOOaJKPrEkFHkxC45OQJ3DB/BlWxCHWJKHWJKP/70hM5derIoKNJnhY1/gewuy3F7vYU08fUEY3o91/pn7bODNv2djBlVA3V3c7IpTx6WtS4JGPgUtlG1SUYpbNuGaC6qhgzx9UHHUOOQUMoIiIhpQIXEQkpFbiISEipwEVEQkoFLiISUipwEZGQUoGLiISUClxEJKRU4CIiIaUCl4LkcuW75YKUnj5/Q5MupZde/WH9K9z041Uc6MxwVuNoFi9MMqI2HnQsKdBzW/Zwww+aaN3fyazx9dx17VlMGVUbdCwpEZ2BS4+27T3Ix+9dyb6ODDmHlZt3c/PPnws6lhSoI51l4Z3L2bG/Ewc27DjA9XfrZnJDSTGLGk81s8fNbK2ZrTGzT5YymATvr68cIBb9+5dIOuus2rInuEDSL9v3dpA5bOgk512fUxk6ihlCyQCfcveVZjYMWGFmj7r72hJlk4BNH1NL+rCV7CMGMxt0V7qwGDe8iu53i540qjqYMDIoilnUeJu7r8z/fT+wDphcqmASvOlj6rj10pOIR43qeIQpo2r58ntODTqWFKg2EePbV51BTTxKdTzC6LoEixcedUtpCbGSLOhgZo3AUmCuu+/r9twiYBHAtGnTzmxubi76eFJebZ0Z9nWkGTesWgtChFBHOsvOthTjhlURj+ptrzDqaUGHoj+bZlYP/By4qXt5A7j7YndPunuyoaGh2MNJAOqqYkwcUaPyDqnqeJTJI2tU3kNQUZ9RM4vTVd73uvv9pYkkIiKFKGYWigF3Auvc/SuliyQiIoUo5gz8PGAhcKGZrcr/uaREuUREpA8Dnkbo7v8DaFBURCQgeldDRCSkVOAiIiGlApdB98q+DlZu3k1nJht0lFDaeaCTFc27aU9lgo4iFUZ3I5RB9fTGnXzw+88QMZgyqpYHbzyP6ng06FihsX77Pt59+zIAhlXH+O0nL9DdIOU1OgOXQbV46UYOprO0pbK07Gln5ebdQUcKlR8t38yBzgwHOjPsPZjmiRd3BB1JKogKXAbVzHH1VMW6vsyyOWfyyJqAE4XLcWPrqIl3ffzcYepo3ctb/k5DKDKo/u3iE0hnc6z92z5umH8c08fUBR0pVBbOa2RnW4rlm3bx3uRUzpg2KuhIUkFKcjOrQiWTSW9q0g3lRUT6Y9BuZiUiIsFQgYuIhJQKXEQkpFTgIiIhpQKXivfZB1dz7m2P8eSGV4OOMiD/9dv1zPvPx3h07fago8gQowKXitaeynD3smb+tqeDbz++Ieg4/ebu3P7ES2zb28E3HgtffqlsKnCpaLWJGJefMZnRdQmun39c0HH6zcy45txGRtbG+fAF4csvla2oeeBmtgD4OhAF7nD323rbX/PARUT6r+TzwM0sCnwLeAtwEvA+Mztp4BFFRKQ/ihlCeT2wwd03unsK+DFwWWliiZTO0hdbede3n2R/R3pA//6pDa/yzm89yd6DA/v3IoOlmAKfDGw57HFLftsRzGyRmTWZWVNra2sRhxMZmFG1CSaPrCEeHdiX+4jaOJNH1ZAY4L8XGSwDHgM3s3cDC9z9+vzjhcDZ7n5jT/9GY+AiIv03GPdC2QpMPezxlPw2EREpg2IK/BlglpnNMLMEcCXwUGliiYhIXwZ8P3B3z5jZjcDv6JpGeJe7rylZMhER6VVRCzq4+6+BX5coi4iI9IPeVhcRCSkVuIhISKnARURCSgUuIhJSZV3U2MxageYB/vOxQCXeEFq5+ke5+ke5+qdSc0Fx2aa7e0P3jWUt8GKYWdOxrkQKmnL1j3L1j3L1T6XmgsHJpiEUEZGQUoGLiIRUmAp8cdABeqBc/aNc/aNc/VOpuWAQsoVmDFxERI4UpjNwERE5jApcRCSkQlngZvYpM3MzGxt0FgAz+7yZPW9mq8zsETObFHQmADP7kpmtz2d7wMxGBp0JwMyuMLM1ZpYzs8CnfJnZAjN7wcw2mNmng84DYGZ3mdkOM1sddJbDmdlUM3vczNbmP4efDDoTgJlVm9mfzey5fK7PBZ3pcGYWNbNnzezhUr5u6ArczKYC/wRsDjrLYb7k7qe4+2nAw8CtAec55FFgrrufArwIfCbgPIesBt4FLA06SAUvzr0EWBB0iGPIAJ9y95OAc4CPV8jHqxO40N1PBU4DFpjZOcFGOsIngXWlftHQFTjwVeBmoGLefXX3fYc9rKNCsrn7I+6eyT98mq5VkwLn7uvc/YWgc+RV5OLc7r4U2BV0ju7cfZu7r8z/fT9dpXTUWrjl5l0O5B/G838q4vvQzKYAbwXuKPVrh6rAzewyYKu7Pxd0lu7M7P+a2RbgA1TOGfjhPgT8JugQFaigxbnlaGbWCJwOLA84CvDaMMUqYAfwqLtXRC7ga3SddOZK/cJFLegwGMzs98CEYzx1C/DvdA2flF1vudz9QXe/BbjFzD4D3Ah8thJy5fe5ha5ffe8tR6ZCc0l4mVk98HPgpm6/gQbG3bPAafn3eh4ws7nuHuh7CGZ2KbDD3VeY2RtL/foVV+DuftGxtpvZycAM4Dkzg67hgJVm9np33x5UrmO4l65VispS4H3lMrNrgUuBN3sZJ/334+MVNC3O3U9mFqervO919/uDztOdu+8xs8fpeg8h6DeBzwPebmaXANXAcDO7x92vKsWLh2YIxd3/4u7j3L3R3Rvp+lX3jHKUd1/MbNZhDy8D1geV5XBmtoCuX93e7u7tQeepUFqcux+s6+zpTmCdu38l6DyHmFnDoVlWZlYDXEwFfB+6+2fcfUq+s64E/lCq8oYQFXiFu83MVpvZ83QN8VTE1Crgm8Aw4NH8FMfvBB0IwMzeaWYtwDzgV2b2u6Cy5N/kPbQ49zrgp5WwOLeZ3QcsA2abWYuZXRd0przzgIXAhfmvqVX5s8ugTQQez38PPkPXGHhJp+xVIl1KLyISUjoDFxEJKRW4iEhIqcBFREJKBS4iElIqcBGRkFKBi4iElApcRCSk/j+nSBcr6gg5ugAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(x,y,s=8*y);         #二维气泡图,s=8y"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5.1.3 三维散点图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\kit\\AppData\\Local\\Temp/ipykernel_16656/3617781357.py:5: MatplotlibDeprecationWarning: Axes3D(fig) adding itself to the figure is deprecated since 3.4. Pass the keyword argument auto_add_to_figure=False and use fig.add_axes(ax) to suppress this warning. The default value of auto_add_to_figure will change to False in mpl3.5 and True values will no longer work in 3.6.  This is consistent with other Axes classes.\n",
      "  Axes3D(fig).scatter(X, Y, Z);\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "X, Y = np.meshgrid(x, x)                #从坐标向量x,y中返回坐标矩阵\n",
    "Z = np.sin(np.sqrt(X**2 + Y**2))        #Z=sin(sqrt(X^2+Y^2)) \n",
    "from mpl_toolkits.mplot3d import Axes3D \n",
    "fig = plt.figure() \n",
    "Axes3D(fig).scatter(X, Y, Z);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5.1.4 三维曲面图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\kit\\AppData\\Local\\Temp/ipykernel_16656/932890556.py:3: MatplotlibDeprecationWarning: Axes3D(fig) adding itself to the figure is deprecated since 3.4. Pass the keyword argument auto_add_to_figure=False and use fig.add_axes(ax) to suppress this warning. The default value of auto_add_to_figure will change to False in mpl3.5 and True values will no longer work in 3.6.  This is consistent with other Axes classes.\n",
      "  Axes3D(fig).plot_surface(X, Y, Z);\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from mpl_toolkits.mplot3d import Axes3D \n",
    "fig = plt.figure() \n",
    "Axes3D(fig).plot_surface(X, Y, Z);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5.2 Seaborn 统计绘图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#!pip install seaborn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "import seaborn as sns  #加载seaborn包"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 5.2.1  seaborn绘图特点"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5.2.1.1  统计图的绘制"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5.2.1.2  分组图的绘制"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5.2.1.3  分面图的绘制"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 5.2.2 seaborn中的统计图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>学号</th>\n",
       "      <th>性别</th>\n",
       "      <th>身高</th>\n",
       "      <th>体重</th>\n",
       "      <th>支出</th>\n",
       "      <th>开设</th>\n",
       "      <th>课程</th>\n",
       "      <th>软件</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1510248008</td>\n",
       "      <td>女</td>\n",
       "      <td>167</td>\n",
       "      <td>71</td>\n",
       "      <td>46.0</td>\n",
       "      <td>不清楚</td>\n",
       "      <td>都未学过</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1510229019</td>\n",
       "      <td>男</td>\n",
       "      <td>171</td>\n",
       "      <td>68</td>\n",
       "      <td>10.4</td>\n",
       "      <td>有必要</td>\n",
       "      <td>概率统计</td>\n",
       "      <td>Matlab</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1512108019</td>\n",
       "      <td>女</td>\n",
       "      <td>175</td>\n",
       "      <td>73</td>\n",
       "      <td>21.0</td>\n",
       "      <td>有必要</td>\n",
       "      <td>统计方法</td>\n",
       "      <td>SPSS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1512332010</td>\n",
       "      <td>男</td>\n",
       "      <td>169</td>\n",
       "      <td>74</td>\n",
       "      <td>4.9</td>\n",
       "      <td>有必要</td>\n",
       "      <td>编程技术</td>\n",
       "      <td>Excel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1512331015</td>\n",
       "      <td>男</td>\n",
       "      <td>154</td>\n",
       "      <td>55</td>\n",
       "      <td>25.9</td>\n",
       "      <td>有必要</td>\n",
       "      <td>都学习过</td>\n",
       "      <td>Python</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           学号 性别   身高  体重    支出   开设    课程      软件\n",
       "0  1510248008  女  167  71  46.0  不清楚  都未学过      No\n",
       "1  1510229019  男  171  68  10.4  有必要  概率统计  Matlab\n",
       "2  1512108019  女  175  73  21.0  有必要  统计方法    SPSS\n",
       "3  1512332010  男  169  74   4.9  有必要  编程技术   Excel\n",
       "4  1512331015  男  154  55  25.9  有必要  都学习过  Python"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#（1）读取绘图用数据\n",
    "import pandas as pd\n",
    "BSdata=pd.read_excel('DaPy_data.xlsx','BSdata');BSdata.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "#（2）中文字体段时需设置字体\n",
    "import matplotlib.pyplot as plt             \n",
    "plt.rcParams['font.sans-serif']=['SimHei']; #设置中文字体为'黑体'\n",
    "plt.rc('axes', unicode_minus=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 5.2.2.1 箱线图（boxplot）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxplot(x=BSdata['身高']);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxplot(y=BSdata['身高']); #竖着放的箱线图，也就是将x换成y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 分组绘制箱线图，分组因子是“性别”，在x轴不同位置绘制。\n",
    "sns.boxplot(x='性别',y='身高',data=BSdata);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### 5.2.2.2 小提琴图（violinplot） "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.violinplot(x='开设', y='支出', hue='性别', data=BSdata);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### 5.2.2.3 点图（stripplot，航线图） "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.stripplot(x='性别', y='身高', data=BSdata, jitter=True); "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.stripplot(x='性别', y='身高', data=BSdata, jitter=False); "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### 5.2.2.4 条图（barplot） "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(x='性别', y='身高', data=BSdata); #不同性别身高均值标准差图"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### 5.2.2.5 计数图（countplot） "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(x='开设', hue=\"课程\", data=BSdata);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### 5.2.2.6 分组关系图（factorplot） "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 648x144 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import warnings  \n",
    "warnings.filterwarnings(\"ignore\")            #忽略警告信息\n",
    "sns.factorplot(x='性别',col=\"开设\",col_wrap=3,data=BSdata,kind=\"count\",size=2,aspect=1.5);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### 5.2.2.7 概率分布图（distplot）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "BSdata['身高'].hist(); "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.distplot(BSdata['身高'], kde=True, bins=10); "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#针对双变量，可使用Seaborn中的jointplot()函数。\n",
    "sns.jointplot(x='身高', y='体重', data=BSdata); "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 540x540 with 12 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.pairplot(BSdata[['身高','体重','支出']]); #配对散点图"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 5.3 ggplot 绘图系统"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5.3.1 ggplot与plotnine包"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 5.3.1.1 包的安装"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "#!pip install ggplot    #在系统上安装ggplot包\n",
    "#!pip install plotnine    #在系统上安装plotnine包"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 5.3.1.2 包的加载与设置"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "from plotnine import *    #加载和调用ggplot所有方法\n",
    "theme_set(theme_bw(base_family='SimHei')); \n",
    "#设置图形主题背景为白色bw、中文字体为黑体SimHei"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5.3.2 ggplot 基本绘图 "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 5.3.2.1  基本定义"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 5.3.2.2 ggplot中的图层 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<ggplot: (17305736)>"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "GP=ggplot(BSdata,aes(x='身高',y='体重')); GP #绘制直角坐标系"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<ggplot: (17306649)>"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "GP + geom_point()  #增加点图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<ggplot: (17305817)>"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "GP + geom_line()   #增加线图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<ggplot: (17401378)>"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "GP + geom_point() + geom_line()  #增加点和线图"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 5.3.3 常见统计图绘制"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 5.3.3.1 直方图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<ggplot: (17411199)>"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ggplot(BSdata,aes(x='身高')) + geom_histogram()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 5.3.3.2 分组散点图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<ggplot: (17453695)>"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ggplot(BSdata,aes(x='身高',y='体重',shape='性别')) + geom_point() "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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cZBhG/HXieUmM56YrembP3PTcGIahq4aV6A8bt+jDxiaZMvTV/BydX1LY49+Rntm9VHpeUm2v3ECQ9oEPAOAOIY9HPx1eGj/WLFXCCeAGBD4AQEoh6AF9j4McACRVzLYVTaGzAwFgIGKED0BStMYs/WHTZr27vUmSdGh2SDPLByvk8ThcGQAMPIzwAUiKP27arEXbm2RLsiUtaWjWvRuYRBcAnEDgA9DnYratd7Y3qfN5eFFJixub1cb8aADQ7wh8APoVR/MBQP8j8AHocx7D0KHZIXk7nWzpkTQuM0NBJsQFgH7HJy+ApJhZPljjMkPx2wdmZugnQ0scrAgABi7O0gWQFCGPR9eMKFObZcmWGNkDAAcR+AAkVYCgBwCO45MYAADA5RjhA5AUdiSimkf/qoaFb8q2bWUdfoSKzr1Ipt/vdGlpq3Xt59py3x8U2VwlMy9PxedfrMzxE50uC0AaYIQPQFJU//UBbXv9ZVktzbJbW9Tw1gJteeCPTpeVtiK1Ndp02y0KV2yUHY0oVlOtyrvvUOvnnzldGoA0QOAD0Odsy9L2N1+XYrEvFsaianz7v7LCYecKS2NN778jOxaTdrouccN/FzhUEYB0QuAD0Pcsq/1fIp1DIHrMjkZlGMZOC23Z0YgzBQFIKwQ+AH3O8HqVMfZgyeP5YqHHo8B+o2RmZDhXWBoLHTJedjTabXnmhEkOVAMg3RD4ACTF4Mt/rMDwEfHb/iHlKv3RVc4VlOYCw0dq8GU/kuH1tS8wDBWcdY4yJx3mbGEA0gJn6QJICm9Orspv/B9Ft9ZKti3voAIZzMm3T7KPOEqZkyYrsrVWysySPzvb6ZIApAkCH4CkMQxDvoJCp8twFTMQkL+kVNEEu3cBYFf4ug0AAOByjPABA0RrzNJfqqq1pKFZAdPUqYV5OmFQ7h7XsyMR1TzxqJree0fyeJR73EnKO+Wb7J4FgDRC4AMGANu2def6Sq1oblHUlqSY5lZUS9IeQ9/mB/6oxnffjk+nUvvEo7IiYRWc8Z0kVw0A6Ct8RQcGgIpwRMuaOsJeO1vSM9V1u10v1tSkxoVvdZ07z7K07cXnklMoACApCHzAANC2i0mQWy074fIOdrgt4XKulgEA6YXABwwAZQG/sjymOl+nwStpXNbuJ0H25ObJW1gkGZ0+KjweZRxwYFLqBIBkC4fDWrt2rWx791943YbABwwAQdPUNcPLFPJ88ZbfLxTU9LLi3a5nmKbKrrxGnry8+DJ/aZkGz/hhskoFgKRauXKlRo4cqebm5m4/e/jhhzV69OiE6x1xxBEyDKPbv50f59NPP0243GmctAEMEKNDQc0eM0Ib2sIKmoaGBPwyd742awL+IeUa/r93K7xpgwzTI3/5UBmdL5kGAGkkGAx2+W99fb3GjRund955RxkZGcrYxeUfA4GAZs+erXPOOUeStH79ek2YMCH+ODNmzNDPfvYzBQIBSZLf70/2r9IrjPABA0jQY2p0KKihwUCPwl4H0+9XcOT+CgwfQdgDkLZaWlrk9baPdf3zn//UunXrtHjxYrW1tamsrEwej0fmjimnbNtWuNPxyoZhKBQKKS8vT3l5ecrJyZGk+P0ffvhh1dfXy+jFZ2t/YoQPAAAMCIcffriuvvpqSdKCBQv05ptvqqSkRNXV1V2CWsf/77///lq9erUkKRaL6f3331dWVpYkqbq6fWory7Jkmqb8fr98Pl9//jq9QuADBgg7GtXWeU+o6aPFMgMB5Z1yqrImfyl527NtbX91vra/+bpk28o+aopyTzwlJb/9ftrUoie2bNX2aEwHhIKaVlLY5XjHvhbeXKXav/9Nkc1V8pUNUeHZ53IJOiDJLMvS6tWrNWbMGEnSRRddpGnTpikvL0+zZ8/W5Zdfrnnz5umXv/ylFi9eLMuy1Nb2xUwF48eP16effqoFCxaosLBQhmHohBNOUDgcju/WTWUEPmAAsG1bVX+4V02LF8Xn1KtavVKD/9+PlP3lo5Kyzbrn5mnr049LO6aEaVu3RtFt21R45tlJ2d7eWtHcolvXbJKt9rkJK8JhrW5p06/2L5c3CeE0urVWG2+5XlZrq2RZCldVqPXTTzTs13fJs2MXEYC+t3TpUmVlZam0tFRSe4C7//77dfzxx+uZZ57pdn/TNLsczzd79mxJ0gEHHKBTTjlFP/vZz/qn8D5C4AMGgMiWzWpa9G7XhbatrU8/npTAZ9u26p55Kh72JEmWpfrnn1HBt86U4U2dj555W+riYU+Sora0trVNy5taNC4r1Ofb2/b6K+3zGHY8N7GYrJZmbX/rDeV//dQ+3x6Adl6vV9dff32XZQcccID++c9/KhQKdZumJRKJKBaLKRgM6u2331ZNTY28Xq8ikYi2bt2qF198UZKUmZmpY445pt9+j72VOp+6AJLGampKvLw58fJ9Fo3KjkQSbNCS1dYmTwoFvoZYTDvPxuUxpKZY4smq95XV1NQ1CKs9bCbttQAgSTrooIN00EEHae3atfFl+fn5GjlypEKhrl/uOg49+f73v6+HH35YTzzxhF5//XV5PB6tW7dOzzzzjF599VXV19crGAxq8eLF/fib7B3O0gUGAH9pqYzATseYeDwKjjogKdszfD75y8ols9NHjGnKW1gkT2ZmUra5tw7MzOj2zdeypRHB5EypENx/VPeFsVji5QCSbv/991dLS4ssy9LTTz+tCRMmyLZtRSIRPfDAA5Kku+66S++9955efPFFWZal5557Tm+//bZ+85vfxKdfiUQiikajTv4qu0XgAwYAMyOk0h9dJcPvbw9hhiHf4BIVX3hp0rZZ8sMr5cnOab9Kh2nKk5ml0p9cnbTt7a3vFg/SmFB7GPao/UPx/w0pVkkgOYEv64ijlfPVE9pv7JjiJu/rpypz4uSkbA/A7hmGoWAw2O2EMq/X220uvRdeeEGDBw/WiBEjJLVP89IxOtjW1qbW1tZ+qXlvpM5+FQBJFTpkvIbfca/a1n4mIxBUxqgxMpI4hYC/bIiG3z5LrZ+tkm3ZCu4/OuVG9yTJb5q6YeQQrWpuVUPM0rCgX8X+5D0vhmGo+PyLlfuVExSprZGveLAC5UOTtj0AfaOqqkrXX3+9fvCDH8TDYUtLizJ3fK51jO513mWcSgh8wADizcuTtx9HksyMkEKHTOi37e0t0zB0QOburyvc1wLDRygwfES/bhOA4pMpRyIRGYahSCSScITPtm21tbXJ4/Hoo48+0jnnnKPBgwfrmmuuUXV1tZYsWaJnnnlGxcVfXKJy9erVeumll+T3++VJsUnqHQt8Tz/9tJ5++un47XA4rCOPPFJHHXWU5syZI9M0NXPmTE2YkPp/LAAAQHromFuvra1Nb731lk477TQFg8H4FTMkKS8vT7Ztq7W1Vffee69mz56t4cOH64knnlAwGFRtba2++c1v6ktf+pJuu+22+HpnnXWWPv74Y1100UUpN+eoY4Fv6tSpmjp1avz27bffrvHjx2vWrFm6+eabVVZWpptuukl33HFHyl2PDnBS1Lb1bHWdPmlqUbbXo9MK8zQyI3mTftq2rYYFr6nx/XdleD3KOfa4pB9vtqShWfO31quhpVVH+bfrpILclPvwlNqnu9n67NOK1tYoMHykBp3xHZlpMAErMJCNGzcuPgXLySef3OXyabty5plnKi8vLz5qN2TIEG3fvj1+3dwOzz77rPLy8uK7eVNJSuzSXbdunWpqaiRJY8aM0dixYyW1vyjLli3TpEmTnCwPSBm2beu36yr1UWOzYpIMSe9sa9Qv9yvX6FBygsbWpx9X3XPz4lOJNH24SMWX/EA5Rx+blO29va1R92yoik+VsrKqRpsjEZ1XWpSU7e2tSPUWrb/pWtnhNsmy1LLiUzUv/UjlN/5KJl9SgZSyaNGipDzu5Mldv/wOGTIkKdvpCykR+ObNm6czzjhDVVVVGjlyZHx5UVGRKisruwS+yspKVVZWSmq/jl3TjvnFLCs5c2b1lm3bsixLlmWl5IiEUzpen1R5nVJJb3pmdXOrPmxs/mJdSZakv2+u1fXDS/u8Nqu1VXXPPi11npDUtlXz2MPKOnJKn29Pkv5aWd1lXjxL0r9qt+m0gjzleFPnmJitLzwbD3uSpFhU4YqNalz0rrKSdPWSDnzOJMbnTGL0C6ReBr5wOKxrr71Ws2bN2u39brzxRv3qV7/q0WM2Njbq448/1syZM/Xkk092mfwwGAyqvr6+y/3nzJmjW265JX777LPbL9NUVVXVw98CTtqyZYvTJaS1deGoTLWHoA62pOqW1qS8B6z6uq5hr2N5U2PS3nMN0VjC5Ws2b9bgJF7ftrfaqqq6TaAsw1Tdpo1q5PPIUXzOYFc6rqPbF1auXNlnj9UfehX4PB6P5s6du8vA98gjj+icc87RH//4xx4HvrfeekuHH364vF6vsrKyurxRw+Fwl4MoJemyyy7T6aefLql9hG/+/PmSpJKSkt78Kklj27ai0ai8Xi/fpDqxLEtbtmxRcXFxt9d0oOtNzxjhiOzVG7os80g6IDtTJSXFiVfal9qKirQuFJLV/MWookxT/rLypL3nhrVs0uctbV1CbcAwdGBpifwp1Dt1Yw9U3YpP4tcmliTFoio8eJwykvx5xOdMYnzOJJaK/cIgTf/rUeB7++23VV1drdNOO03eHZdEuu666+KnMYfDYU2bNk3XXnutzjnnnG6XKNmdt956S2eeeaYkafTo0XrjjTfiP1u1alW34/dKS0vjFz6uqKjQwoULJSll3ty2bcs0TZmmmTJvrFTS8dzgC73pmdJgQBeXFen+imp5DUOWbask4NP5pUXJeV5NUyU/vEqV//e/km2315oRUskPfpy013Fm+WD9cs0mNUZjMiTJkK4YVqJgCl2OTZIGff00tXzysVpXrpDh8ciORpX3jdOVeeDBSd82nzO7x+dMV/QLpB4GvjvvvFOHHXaYTjvttPiyWbNm6ZxzztHf/vY3jR07Vl/60peUlZUlqefhq62tTStXrtRBBx0kqT3wNTQ0aN68eSooKNCiRYs0ffr03v5OgKudOChXY0JBfdbSpkzT1MTsUFJHvkIHHaJht81Sy4rlMkxToUPGt19BI0lKA379dvQwLd7epNr6eh1eOlilwcCeV+xnhs+nIT+/Uc0fLVZ0W70CQ4YqOGq002UBQEI9CnyHHnpot2MiMjMz9eCDD2revHm68MIL2x+sl9/Aly9fruHDh8fXMwxDN9xwg+bOnav6+npdddVVys3N7dVjAgPBsGBAw/oxBPkKi+Qr7L+zZLM8Hh2Vm6WqlkYNTuJVL/aVYZrKnHio02UASGFLlizRRRddpIULF3abxqU/9SihjR49WkuXLu3zjU+cOFETJ07ssqxj/j0AAIB09/LLL2v8+PGOhj2ph4Fv6NCh+vDDD3Xvvfeqra2t238XLFig5cuXq7a2Vvfee2+PJjEEBjo7GtW2l19S67o1MrOzlX/yN+UbVOB0WWktvGmjtr02X1ZLizLGHqTso4/lmCUAPWJHImpZ+KZiNdXyFBYp48gpfXK98ccff7zL1Tic0qPAV1xcrA0bNujpp59WJBLp9t+PP/5YGRkZ2r59e3wZgF2zLUsVd9+hluXL2s/y9HjU+OYbGnrr7fIVFDpdXlpqXfOZNv36ZtmWJdm2Gv67QG1rP1fRuRc5XRqAFGdHItp69x2KbvpiFoSWdxdq0E9+1uvQV1VVpeOOO06hUEi2beujjz7ST3/60/iXz+bmZgUCAdm2rRtvvFHf+c53+vR32ZUeBb7CwkIVFRXp1Vdf1aBBg7r8Nz8/X5dffrn2339/3XjjjXr11Ve7TJ4MoLvmpUvU8snSTpP2xmS1tqju2adVfOGlzhaXpmoeeUh2LPbFvIG2rW3z/63cE0+Rv6TvJ6UG4B4tC99sD3udplmKblyvloVvKnTscb16rJKSEi1fvlySdPfdd2vVqlWaPXu2pPaTVYuKirRy5cp+n06uR4EvNzdXjY2Nya4FGDCiW7e2T+XReeLeWEyRaiaM3VvR2pqEk0RH67YS+ADsVqymOvHy2pq9fkzbtvXAAw/oySefjC974403NGnSJEfmDu7xXA7RaLTL5WpaW1u7HMMniV25QA/5y4bIjka7LvR45C8f5kxBLuAfMlQyd7r0mmHIPzg1JmUHkLo8u5iFwLMPh9i88sor2rBhg9599121tbVJku69915ddtlle/2Y+6LHgS8QCKiuri5+++ijj9b8+fP1ta99Ta2trSoqKopf1zYWS3xpJADtMsaMVe7xX5MMo/34EI9XvuLBGnRG/xzL4UZF50+XJytL8nrjx9wUnnOBvJwIA2APMo6cIu+QoZLHE//nLR+mjH24ZvgJJ5yg119/XQsXLtTYsWN16aWXav369Zo2bVofVt5zPZ4477bbblNmZmY8zP3nP//pdp+rr75aktTQ0NBH5QHuVXjuhQpNmKi2dWtlZGUr58gp8gSDTpeVtnxFxRr26zvV+N7bslpbFRx9gDJGH+B0WQDSgOHzadAVP28/S7e2Rp6Cwj45S3f8+PH6/e9/r2OPPVYzZsxQfn6+pk+fruuuu65Pr+vbEz0OfNOnT1dbW1u3efM6+/GPfyxJ+uY3v7nPhQFuZxiGMsdPUmjcREWjUZkpdumwdOTJzmkfOQWAXjJ8vl6foLErtm1r9erVWrBggR566CGZpqm33npLo0aN0ty5c3Xcccfp5JNP1j333KPs7Ow+2eae9Op6TIFAQI899ljCn913333x0b+HH3543ysDAABIQw888IAuvvhirVy5UrNmzdIrr7yigw8+WIFAQDNnztQnn3yiAw88MH5J2v7QqyGFSCSiUaNGxY/V6/D444/r8ssv1/Dhw/W1r/HtGkgm27bV9MF7al29SmYopJxjvipvXn6P1m1eukTNnyyTGQgo+8gp8hUPTnK1/asmHNEb9Q1qsSwdmJmhQ7MznS6pT8VsW6/XbdemtrDyPaZOKMhThsez5xUB9KuLL75YF1988S5/npubq5/97Gf9WFEvA5/P55Pf7++y7L777tOPf/xjzZ49WyeddFKfFgegu9rHHlb9Sy9IpikZUv2L/9LQX/5GvqLi3a5X9/yzqn38kfYzWQ2p7vlnVH79LQoMH9E/hSfZptawbvh8gyK2LdnSczX1+k5Rvs4c7I6TNizb1m1rK7S8qUWSZEh6dVujfr3fUAU9vdpZA2AA6vWnhGEYsm1bL730ko499lj96le/0osvvqgLL7yw3/ZDAwNV28YNqv/3vyTbkmJRKRqV1dKimkf/utv1ovX17WHPtuPr2ZGItvxlbj9VnnwPVFarzbIVtaWoJFvSE9V12hJ2x3RR/93WqOVNLYpJiqn9d9wcjuiF2npnCwOQFnp9lHhDQ4OKi4tVVlamGTNm6NJLL42P+nk56BxIqmj15vYROqvT1EdWTOGqit2vV1vdfVJiy1KkenMSqnRGVTgsK8Hy6nBExf59vx6m0zaHIzINQ7FOr2PUbl8OAHvSo4R2xBFHKBgMyjRNxWIx5efna9CgQXriiSe6zCDd3NysY489Vq2trXr33XeTVjQwUHmLBncNe5JkevZ4JQlvQZFkGF1Dn2nucTdwOhns96kuEusW+opcEPak9t/P2im0ew25IswC/WXlypVOl+CYHgW+n/zkJwoEAjJNU6+99pokacyYMTrppJPk2zFHjWVZevfdd3XllVeqpaUlaQUDA1mgfKhyv/YNbfvPi5JpSIYhMxBQ4dnn7XY9b16eBn13mrY+/mj8GD7DNFV8wSX9VHnyXVRapBs/36iobcu2JUvSt4vyXROIjszN0mt127scw1fs8+kbBXmO1gWkg8mTJztdguN6FPg6zwqdkZGhM844Q88++6z+9a9/6YorrtAVV1yhWCymWCymqVOnJq1YAFLhtPOUMfoAtX62SmYoUznHfEXe/EF7XG/QN05XoHyYWpbvOEv3qCnyFbvnsmNDgwHdNWqYXq9vUKtlaWwoQ5Nz3HOWrscwdN2IMr1at10VbWHlm6ZOLMzjhA0APdLrg+4CgYDuvPNO3XnnnXr22Wd1/fXX69FHH9X999+vyy+/PBk1AujEMAxlfenLyvrSl3u9bub4icocP7Hvi0oRhX6fvlO85/CbrjyGoRMH5cq2bUWjUXlNwh6AnulV4Gtra1Nzc3P89mmnnaYTTzxRl156qU466aSEl1sDAABw0qJFi5LyuOm0q7hHXw/vu+8+vf766/J6vXrqqae6/CwjI0MPP/ywjjvuOK6wAfRS89Ilqnv+GTW+9YastjanywEAuFSPRvhefvllXXnllSorK9PRRx+tJ554ott9DMPQpk2bdOGFF0qS/vznP/dlnYDrVP/tL9o2/0UZXq9sy9L2l57X0Bt/JTMj5HRpAOBKY8aM6bPHSrczfnsU+B577DGFw2E9+eSTuv/++/XKK69o+PDhuuSSSxQMBrvc1955ri8A3bSsWqFt81+UbFt2pH0etcjmzar951MqOvtch6sDALhNj4/h8/v9mjZtmqZNm6b3339fP//5z3X//fdr/vz52m+//ZJZI+A64YpN7SN7kU6T5saiCm9Y51xRAADX2qtLYxx22GF65ZVX9NprrxH2gL3gzc+XHes+gbKvsMiZggAArrZP5/R/9atf7aMygIEldMgEZRx4iOTxtC/weGQGg8o//dvOFgYAcCUufgs4wDBNlV35c9XP/7fa1q2RmZ2j/JO/IV9BodOlAQD20fz58/Wtb31LY8eOlSTV1tZq27Zt8b2iFRUVOv/883X77bf3W00EPsAhhter/FO++cUkul7ejgDglIht683GFlVHYiryeTQlK0M+w9irxwoEAjrkkEP09ttvS2qfueS5556Lz3Lyy1/+st9PcuUvDAAAGNAitq07qrZqQzgaX7awsUU/Kxm0V6HPMAwtXbpUhx12mKQvRvg6bldUVGjGjBl9U3wPEfiAHWzb1tKmFlWHoyoJ+HRgKCijh2/0llUrFKnYJG9BgTIOGicjyZe8atu4QW1rPpMZCik0bqJMvz+p2wMAN3uzsUUbwlF1PpVufTiqNxtbdFx27+dGtW2bET4gFVm2rXs3bNY72xvlNQxFbVtfzcvWjCHFuw19tm2r5m9/1raXX2qfZiUaU2j8RJX++KcyOk7I6GPbXpuv6r/c3769WEy+klKVX3+LPFlZSdkeALhddSSWcHlNNPHyPQmFQgoGg/GTWy3LkmmaXU52Peecc/bqsfcWgQ+Q9Hp9g97b3ihb7UP7HcsmZGfqiNxdB6nmjxZr2yv/6TKBcvPSJdr26n+Ud+IpfV5npHqLqv9yf7cJm2se+6sGX/KDPt8eAAwERb7EX9ALvXv3xX38+PF67bXX4reHDx+uhx9+WMccc8xePV5fIPABkta2tGnnwXXTkNa0tO028LWtWyPD45FtWV8stCy1rVublDrDGzdIhiF13hUQi6r188+Ssj0AGAimZGXovzt263YY5vdqSlbGXj3e1KlTtWHDhvgeovXr1+tHP/pR/OeRSESff/65mpube3zo0L4i8AGScrwemYZk7ZT6cvfw7c6TkyN755VMjzw5uX1c4RfbU+dwKUmGIW9eXlK2BwADgc8w9POSQXqzsUU10ZgKvft2lu5zzz0X//93331Xl156qRYvXhxf9vHHH+vMM8/st7An7ePEy4BbnDQoV5kejzrinUdSnterr+Rn73a97COmyFdYKHl2fHcy2ydQzjvx5KTUGRi5v0LjJ30xYbNhSIahgm9/LynbA4CBwmcYOi47pO/mZ+u47NBeh73O1qxZoxkzZujaa6/tsnzdunUaMWLEPj9+bzDCB6h9hO/2/YfqiS1bVRWOaEjApzOLC5S5hxMvzGBQ5Tf9j7Y+/YTCGzfIW1ysQWd8R978QUmp0zBNlf74p6r71z/VsmK5PFnZyvv6qQqO3D8p2wMA9M727dv1+9//XgsWLNDq1at13XXXadq0aZLad+Xec889euyxx3T66af3a10EPmCHfJ9Xlw4p7vV6nswsFZ17Yd8XtAuG16tBZ3yn37YHAOi5nJwcDRs2TDfccIOOOuqoLrttfT6fysvLdcMNN+i0007r17oIfAAAAH3o3HPP3eXPzj777H6s5AsEPqCThvfeVnj9WgX3G6XMSYc5Xc4uRbfWqm39WpmhTAVHjUn6RM97qyVmaXVLqyxbGh0KKJSkuQkBALtH4APUPinmxpuuaZ/2ZIfA/qM19MZfOVhVYo3vvq2qOb9rn5rFshQcfYDKfnqdzGDQ6dK6qGgL61drNql+x8Sl2R6PbhxZpqHBgMOVAcDAQ+ADJNX87S9dwp4ktX22SrVPP66Cqd91qKruoltr28Ne7IvZ31vXfKbaxx9R0XnTHaysu1nrq7QtGovPb9gQi+mudZW654ARTpYFYABbuXKl0yU4Ju0DX1ZWlrxeb79fk25XOupIlXpShW3b8dcpFZ+b1pXLEy5vXvaxBn3rzKRuuzc907pubddJlyUpGlXLp8tT6nmNWLY2toW7LLMlbY5E1RiN7vHsZyn1e8ZJfM4kRs8klor94vX2b/yYPHlyv24vFaV94Js0aZLy8/MVjUb3fOd+FIvt3fX33Cw/P1+WZcnaeeLgFGAEE8+mbmSE+q23etIzdiDQfeJlSUZmZmq9B2xbXkOK7jwntSSPZSnawz88qdwzqYDPme7omV1LpX7Jz893uoQBJ+0D34cffqhx48apqKjI6VIktX+DisVi8ng8/TqDdqqzLEu1tbUqKCiQmYInGBR+71xt+p8buy40DBV+75ykfxPtTc9kHnCgAqPGqG3N51IsGq9z0Onf7vdvzHsytTBfT1bXqePPrinp1II8BX2+Hq2f6j3jJD5nEqNnEkvFfqmurna6hAEntf5C7IXGxkZFo9GUaeIOhmGkXE1OMgwj/jql4vOSMWq0Sq++Xpvvmy2rqUmerGyVXH6FguXD+q2Gnjw3hsejIVdfr9p/PKKWFctlZmVp0OnfVujgcf1UZc99u3iQsr1evVa3XZZsHZuXo68X5Pb49U/1nkkFPDdd0TO7l0rPS0rtkRgg0j7wAX0l85Dx2u+eOU6XsUdmMKii81PrBI1EDMPQ1wpy9bWC5FxXGADQc4x5AwAAuByBDwAAwOUIfAAAAC5H4AMAAHA5Ah8AAIDLEfgAAABcjsAHAADgcgQ+AAAAlyPwAQAAuByBDwAAwOUIfAOQbduK1m1VdGutbNt2upykaI5ZqmqLKGxZTpcCl6PXAKQDrqU7wMS2b1fF3Xeo7fPVkqTA8JEqvfLn8ublO1xZ37BtW09t2aonqutkSwoYhn48tESTczKdLg0uQ68BSCeM8A0wVX+4R23r1sRvt21cr8rfzXKwor711rbG+B9gSWqzbc1aX6mKtrCjdcF96DUA6YTAN4DY0ahaPv1EisW+WBiLqe2zVbJaWpwrrA8t2t6knXdSm4ahpY3u+P2QOug1AOmEwDeQmKZkGIl/5vH0by1J4jO7/362bHl39XsDe4leA5BOCHwDiGGayj762K7hzuNV1uFHyvT7nSusD30lL1ud/9yakgKGqUOzQ06VBJei1wCkEwLfAFN8/sXKOfZ4GcEMGYGgso+aouJLfuB0WX3m4KyQrhxWokFej7yGoaFBv27eb4jyfJyfhL5FrwFIJ3wyDTCGz6fiCy5W8QUXO11K0hyek6XDc7KcLgMDAL0GIF0wwgcAAOByBD70i0gkotbWVqfL2CPbthVraur1hNS2bSvW3CybyXcBACmIXbpIqlgspjcfuE+l/31dpm3r/cJiDfnx1RoybJjTpXXT8M5/teXBP8lubZWZEdLgGTOVOWnyHtdrXrpEVX/8nazGRhn+gIouuFg5Rx/bDxUDANAzjPAhqf772KMqWfiGzB0jZrm1Ndp8129SbrSvZdUKbf7j72TvqMtqaVbl736rtnVrd7teuGKTKv7vDlmNjZIkO9ymLff9Qc2ffJzskgEA6DECH5Iq+P7b8nTazemxLeVsr9eGz1Y7WFV3TYvea5+nsDPTVNPiRbtfb8kHMnZezzDU9P57fVwhAAB7j8CH5BqIc9AOxN8ZAJDSCHxIqrbDj1Ks0whYzDC1LTdfw0aNcrCq7rIO+7K08wkXlqXMQw/b7XqZEyd3P8HDtpX5pS/3cYUAAOw9Ah+S6sjvfk+bpxwfD311xYNV9vMbFAgEHa6sq+Co0Sq5/AqZofarJJhZ2Sr9yc8UGDp8t+v5S8tUdtU18uTkSpKMYIYGz5ip0IEHJ71mAAB6irN0kVQej0fHTr9EkfMu0KZNm3T4sGEydz7mLUVkfenLyjzscNnhsMxAoMfrhQ4ap5H3zpHV1ibD75fBtVQBACmGwId+4fF45E+D6/UahiGjF2Gvs96ERAAA+lNqDrUAAACgzxD4AAAAXI7ABwAA4HIEPgAAAJcj8AEAALgcgQ8AAMDlCHwAAAAuR+ADAABwOQIfAACAyzke+Jqbm3XJJZdo48aNkqT33ntPl1xyiWbMmKElS5Y4XB0AAED6czzwPfroo/ryl7+s8vJybdu2TbNmzdLVV1+tu+66Sw8++KDC4bDTJbpKzLb1WFWNfvDpGv2/T9for5U1ilq202UBAIAkcjTwrV27Vq+99prOPvtsSdIHH3ygMWPGaOzYscrJydG4ceO0bNkyJ0t0nb9W1ujZmnrVRWOqj8b0Ym297q+odrosAACQRF4nN37fffcpMzNT99xzjyZMmKCWlhaNHDky/vOioiJVVlZq0qRJ8WWVlZWqrKyUJFVXV6upqUmSZFlW/xa/C7Zty7IsWZYlwzCcLqcLy7b1n63bFOu0LCbptfrturCkQD4zefV2vD6p8jqlklTuGSfRM7tGzyRGzyRGv0ByMPAtW7ZMy5Yt0wUXXKDBgwfrr3/9q7761a8qFArF7xMMBlVfX99lvTlz5uiWW26J3+4YHayqquqXutNZ1La7hL0OtqRNm6sU7IcPgi1btiR9G3AXega9Rc8A3TkW+JYvX67Jkydr6tSpkqRYLKY5c+bohBNOiN8nHA7LNLvudb7ssst0+umnS2of4Zs/f74kqaSkpJ8q3z3bthWNRuX1elPym9To1k36vKUtHvxMSeUBv0aUliZ1u5ZlacuWLSouLu72mg50qd4zTqFndo2eSYyeSSwV+4VBmv7nWOALBoMqKiqK3/b5fBo1apQ+/fTT+LJVq1Z12Z0rSaWlpSrdEU4qKiq0cOFCSUqZN7dt2zJNU6Zppswbq7Mrh5XqN2srtLGt/WSYwX6frh5e2m/PX8dzgy+kes84jZ7pjp7ZPXqmK/oFkoOBb8KECXrmmWdUV1enzMxMvfTSS5owYYL+85//aN68eSooKNCiRYs0ffp0p0p0pUE+r/531FBV7Ah8pQG/vHwAAADgao4FvqFDh+rss8/Wddddp4aGBh166KE67bTT9OUvf1lz585VfX29rrrqKuXm5jpVomt5DENDgwGnywAAAP3E0bN0jz/+eB1//PFdlpWVlemmm25yqCIAAAD34SAHAAAAlyPwAQAAuByBDwAAwOUIfAAAAC5H4AMAAHA5Ah8AAIDLEfgAAABcjsAHAADgcgQ+AAAAl3P0ShtIL02LF2nbK/+RHY4o89DJyj3xFBlcoFwN0Zj+saVW61vDKvb59N3Bg1Ts9zldFgAAcQQ+9EjD229p85zfS7YtSWpZ+akim6tUdN50hytzVkvM0i8+26DaSFQxSavVqkUNTbpz9DAV+Hh7AQBSA8Mz6JHafzwSD3uSJCumbS+/pNj27c4VlQLe2tagrdH2sCdJMUltlqV/19Y7WBUAAF0R+NAjscbGXSxv6OdKUktDNCZDRpdl1o7lAACkCgIfeiQwfIRkerosM4JBeQuLnCkoRYzMCCjaeeRT7W+qkRlBZwoCACABAh96ZPCMmfLk5koej+T1yvD5VPrDq2T6/U6X5qiJ2Zn6ekGuJMlntI/1HZqdqRMH5ThbGAAAnXBUOXrEV1Ss4b+5S82fLJUdiSo4eox8BYVOl5USzi8t0lG52apoC6vA59VBmRkyDGPPKwIA0E8IfOgxMyOkrMmHO11GShoVCmpUiN24AIDUxC5dAAAAlyPwAQAAuByBDwAAwOUIfAAAAC5H4AMAAHA5Ah8AAIDLEfgAAABcjsAHAADgcgQ+AAAAlyPwAQAAuByXVksBTYsXqfmTpTL9AWVPOVb+kjKnSwIAAC5C4HPY1mef1tan/iGZpiRD9f/+l4Zc/0sFR+7vdGkAAMAl2KXroGh9nbY++XfJtqVYTIpFZUejqn7oAadLAwAALkLgc1C0tqb7QttWpGZL/xcDAABci8DnIG9hkWQYXReapvyDS5wpCAAAuBKBz0He3DwVTjtPMgwZXq/k9crw+1V0waVOlwYAAFyEkzYclve1b8g/dLhaPlkqIxBQ9hFHy1dY5HRZAADARQh8KSB04MEKHXiw02UAAACXYpcuAACAyzHCtxPbtvVBQ7PWtrYp1+vRlNxsBT3kYgAAkL4IfDu5v6Jar9Rtl8eQbEnP1dTrf/YvV5bH43RpAAAAe4Whq06WN7Xo5brtsiRFbClqSzWRiJ7astXp0gAAAPZa2o/wZWVlyev1yrbtfX6sTa1heQ1DkU6PFbWlDa3hHj9+x/36oh43sW07/jrx3HRFzyRGz+waPZMYPZNYKvaL15v28SPtpP0zPmnSJOXn5ysaje7zY+V7DEV3ekN4JBV6Pb1+/Fgsts/1uE1+fr4sy5JlWU6XkpLome7omd2jZ7qjZ3YtlfolPz/f6RIGnLQPfB9++KHGjRunoqJ9n7tuYk6WJmY16qPGZlmSPIaUYZo6c3BBj7+N2LatWCwmj8cjY+eraAxglmWptrZWBQUFMk2OJOiMnkmMntk1eiYxeiaxVOyX6upqp0sYcNI+8DU2NioajfZJE3sMQ1cPL9X8rdu0rjWsXK9HJw/KVZ6v90+TYRgp88ZKBYZhxF8nnpfEeG66omf2jOemK3pm91LpeemLvXLonbQPfH3NYxg6uSDP6TIAAAD6DGPeAAAALscIXx9qW7dGLZ+tloJBZR96mDzBDKdLAgAAIPD1lfr5/1bN3/4sw+uVbVna9s8ild9wqzzZOU6XBgAABjh26faByJYq1fztz5Jty45EpFhMkZpq1Tz2sNOlAQAAEPj6QnjTJmnnM59iMbWu+dyZggAAADoh8PUBT26utPMkn4YhLxNLAgCAFEDg6wOBkfsr89DDJI+nfYFhSKapgjPPdrYwAAAAcdJGnzAMQyUzr1T9v/+llhWfysjMVP7J31Rw+AinSwMAACDw9RXD41H+N05X3tdPUzQa5cLQAAAgZbBLFwAAwOUIfAAAAC5H4AMAAHA5Ah8AAIDLEfgAAABcjsAHAADgcgQ+AAAAlyPwAQAAuByBDwAAwOUIfAAAAC5H4AMAAHA5Ah8AAIDLEfgAAABcjsAHAADgcgQ+AAAAlyPwAQAAuByBDwAAwOUIfAAAAC5H4AMAAHA5Ah8AAIDLEfgAAABcjsAHAADgcgQ+AAAAlyPwAQAAuByBDwAAwOUIfAAAAC5H4AMAAHA5r1Mbvvrqq7Vly5b47d/+9rdau3at5syZI9M0NXPmTE2YMMGp8gAAAFzDkcAXi8W0detWPfTQQ/Fl27Zt06xZs3TzzTerrKxMN910k+644w75/X4nStwrtm1rezQmn2U7l6QBAAB24kgu2bhxo4YMGdJl2QcffKAxY8Zo7NixkqRx48Zp2bJlmjRpkhMl9tq6ljbdub5SNZGoDEnfKMjV90sKZRqG06UBAIABzpHA9/nnn2v9+vW68MILZZqmvve972n79u0aOXJk/D5FRUWqrKxMi8DXFIvpf9ZuUmPMkiTZkl6s3aY8r1enFeU7WxwAABjwHAl8Pp9P06ZN08knn6xNmzbpmmuu0amnnqpQKBS/TzAYVH19fbd1KysrVVlZKUmqrq5WU1OTJMmyrH6pPZFVTS1qjFmyOy2LSXprW4O+WZDrVFkppeP1cfJ1SlW2bcuyLFmWJYMR4Th6ZtfomcTomcToF0gOBb4pU6bE/7+8vFzjx4+Xx+OJhzdJCofDMs3uJxHPmTNHt9xyS/z22WefLUmqqqpKYsW7Vx+JJVwei0QcrSsVdT5RB+gJega9Rc8A3TkS+N544w0ddthh8RG92tpaDR8+XJ9++mn8PqtWrUq4O/eyyy7T6aefLql9hG/+/PmSpJKSkn6oPLE8y9LfV2/QtmhMHd8rTUknFRWoZFCOY3WlEsuytGXLFhUXFycM8gOZbduKRqPyer18++6Entk1eiYxeiaxVOwXBkP6nyOBb8WKFfr88881bdo0LVq0SBs2bNB1112nN954Q/PmzVNBQYEWLVqk6dOnd1u3tLRUpaWlkqSKigotXLhQkhx9c4dMUzeNHKK7N1RpXWtYfsPQt4vydVJBbsq8uVKFaZp8EO/Etu3480K/dEfPdEfP7B490xX9AsmhwDdt2jTdcccdOu+881ReXq7rr79e+fn5uuGGGzR37lzV19frqquuUm5u+hz/Vhrw639HDVPUsmRFo/L5fLyxAABASnAk8GVlZenWW2/ttrxj/r105jEM2QQ9AACQQhjzBgAAcDkCHwAAgMsR+AAAAFyOwAcAAOByBD4AAACXI/ABAAC4HIEPAADA5Qh8AAAALkfgAwAAcDkCHwAAgMsR+AAAAFzOkWvp9rWamhqnS4jzer3Kz89XdXW1otGo0+WknKqqKqdLSDn0zO7RM93RM7tHz3SViv2SSn+3B4q0DnyhUEg+n09PPfWU06VgDxoaGrRo0SJNnjxZ2dnZTpeDNEDPoLfomfTi8/kUCoWcLmPAMGzbtp0uYl/U19erubnZ6TKwBx9//LFOOeUUvfjiixo3bpzT5SAN0DPoLXomvYRCIeXl5TldxoCR1iN8kpSXl0fDpIGOXSxFRUUqKytzuBqkA3oGvUXPALvGSRsAAAAuR+BDvygtLdXNN9+s0tJSp0tBmqBn0Fv0DLBraX8MHwAAAHaPET4AAACXI/ABAAC4HIEPferVV1/VPffc02VZLBbTFVdcoSVLlsSXrVy5UjNnztT06dP1+uuv93eZSCGde2bBggU6//zz4//OOecc/eIXv5BEz+ALO3/OzJ8/X5dcconOO+88PfDAA+o4UomeAb5A4EOfefvtt/WnP/1JOx8W+vzzz6uwsFATJkyQJEUiEd1+++2aNm2a/vCHP+i5555TbW2tEyXDYTv3zDHHHKOHHnoo/u/EE0/UkUceSc8gbueeaWxs1HPPPaff//73mjNnjpYsWaIPPviAngF2QuBDn5k/f77OOuusLsvq6ur097//XdOnT48vW7lypQKBgKZMmaJAIKBjjz1W77//fn+XixSQqGc6bNu2Te+9955OPvlkegZxO/dMZWWlysrKFAwGFQqFNHr0aNXW1tIzwE4IfOgzv/jFL5STk9Nl2UMPPSSv16sHHnhAjz32mCKRiGpqajRy5Mj4fYqKilRRUdHf5SIFJOqZDi+88IJOPPFE+Xw+egZxO/dMSUmJPv30U23cuFEVFRX68MMPNX78eHoG2EnaX2kDqcMwjC63N2/erFdffVVTp07VQQcdpMcff1z19fU64IADulw/MRgMqqmpqb/LRQrYuWc6xGIxvfLKK7rzzjslSZZl0TOQ1L1nsrOzNWnSJP3617+W3+/XhAkTNHjwYC1fvpyeAToh8CFpVqxYoaFDh+qCCy6QJOXk5OiOO+7Q5MmT1djYGL9fOByWaTLYjC989NFHGjZsmHJzcyVJWVlZ9AwS+uijj1RTU6PZs2fLNE3dd999euaZZ1RWVkbPAJ3Q/UiaYDCooqKi+G2/36/MzEyNGjVKq1atih90vXr1ahUWFjpVJlLQW2+9pSOOOCJ+m57BrnR8sewIc6NHj9aKFSvoGWAnBD4kzYEHHqg1a9aooqJClmXpX//6lw455BDl5+ervLxcDz74oBYtWqQXX3yxyx93YNGiRZo4cWL8Nj2DXRk8eLDeffddrVixQqtWrdJzzz2nYcOG0TPATgh8SJrs7Gz98Ic/1G233abzzjtP1dXV+v73vy9JuvLKK1VbW6u//OUvuuiiizRs2DCHq0Wq6DiwfufRGHoGiRx99NGaOHGibr31Vl177bUqKCjQ1KlTJdEzQGdcSxcAAMDlGOEDAABwOQIfAACAyxH4AAAAXI7ABwAA4HIEPgAAAJcj8AEAALgcgQ9A0jz55JNatmzZXq1bX1/PtU8BoI8Q+AAkRSQS0fe//3298cYbvV63oaFBJSUlevDBB5NQGQAMPEy8DKBP/e53v9Nvf/tbxWIxbdy4UeXl5fJ4PF3us2zZMmVmZkqSfvrTn2rJkiXyer1d7vPf//5XOTk5OuSQQ7osD4fDOvfcczV9+vTk/iIA4CLePd8FAHquublZI0aM0GuvvdbtZ2vXrtXIkSPl8/niy84//3w1NjZ2C4W7EovFVFZW1lflAsCAQOAD0KcCgYDefPNN5eXldfuZZVmSJL/fH182YcIESdIjjzyiq6++usvPOti2LcuytGHDhuQUDQAuR+AD0OemTJmy2xE+qT38mWbXw4jLysr0/vvvJ1xv/PjxSakVAAYCAh+AftfW1qaTTjpJf/7zn7XffvtJkrxeryoqKjRixIhu97dtW7m5uf1cJQC4B4EPQJ/b0y7d888/XytXrtTSpUvjge+ss87SWWed1Z9lAsCAQeAD0Ceam5vjZ9ruapfum2++qWOOOUb19fX6+OOPVVRUpBdffFGnnnqqysvLe7SddevWafHixfFj/wAAe0bgA9AnDj/88C6TLBuGscv7vvDCC/Hj9/x+v0pKSrR27doebcfr9SojI2OfagWAgYbAB6BPvP766/J6vd2mV1m1apV++MMfqra2VnfeeadOP/30LidrdP7/hoYG5eTk6OCDD44vC4fD2rhxo5qbmxOuAwDYMz41AfSJgoIC5ebmKisrS1lZWWpubtYtt9yiKVOm6NBDD9UHH3ygcePGdVuv89zv2dnZ8vv9Wrp0afzf888/r2Aw2J+/CgC4DiN8APpMS0uLXnrpJT366KN6/vnndeaZZ+r999/XgQceKKlruOvQcSKHJDU2Nmr06NHdrq7RcWKHbduybXu3u4sBAN0R+ADss2g0qosuukhPPPGESkpKNH36dN19990qKSmR1B4EZ86cqTVr1ig/P7/LuuFwOP7/WVlZWrp0acJtfPLJJ7r44os1efLkHp/gAQBox7V0AfSJjz/+WPX19ZoyZUrCEbhrrrlGlZWVOv/883XiiSfu1Taampri1+AFAPQcgQ8AAMDlOGkDAADA5Qh8AAAALkfgAwAAcDkCHwAAgMsR+AAAAFyOwAcAAOByBD4AAACXI/ABAAC43P8Hs1znYvKWxzwAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<ggplot: (17400528)>"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ggplot(BSdata,aes(x='身高',y='体重',color='性别')) + geom_point()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 5.3.3.3 折线图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<ggplot: (17684008)>"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ggplot(BSdata,aes(x='支出',y='身高')) + geom_line() "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<ggplot: (17547030)>"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#共用一个坐标，绘制不同的y值\n",
    "ggplot(BSdata,aes(x='支出'))+geom_line(aes(y='身高')) + geom_line(aes(y='体重'))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 5.3.3.4 分面图 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<ggplot: (17588264)>"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#在plotnine中可使用facet_wrap参数可以按类型绘制分面图。\n",
    "ggplot(BSdata,aes('身高','体重')) + geom_point() + facet_wrap('性别',nrow=2) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<ggplot: (17856503)>"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ggplot(BSdata,aes('身高','体重')) + geom_point() + facet_wrap('性别',nrow=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<ggplot: (17893885)>"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ggplot(BSdata,aes('身高','体重')) + geom_line() + geom_point() + facet_wrap('开设',nrow=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<ggplot: (17934725)>"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(ggplot(BSdata,aes('身高','体重')) + geom_point() \n",
    "       + facet_wrap('~性别+开设',nrow=3))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 5.4  pyecharts动态绘图"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5.4.1  pyecharts简介"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 5.4.1.1 关于pyecharts"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 5.4.1.2 pyecharts安装与设置"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "#!pip install pyecharts      "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "#加载 Jupyter lab中设置 pyecharts 全局显示参数\n",
    "from pyecharts.globals import CurrentConfig, NotebookType\n",
    "CurrentConfig.NOTEBOOK_TYPE = NotebookType.JUPYTER_LAB     \n",
    "import pyecharts.options as opts                                     #并加载pyecharts选项\n",
    "figsize=opts.InitOpts(width='560px',height='380px',bg_color='white') #设置图形大小和背景色"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5.4.2  pyeharts基本绘图"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 5.4.2.1 仪表盘"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "new Promise(function(resolve, reject) {\n",
       "    var script = document.createElement(\"script\");\n",
       "    script.onload = resolve;\n",
       "    script.onerror = reject;\n",
       "    script.src = \"https://assets.pyecharts.org/assets/echarts.min.js\";\n",
       "    document.head.appendChild(script);\n",
       "}).then(() => {\n",
       "\n",
       "});"
      ],
      "text/plain": [
       "<pyecharts.render.display.Javascript at 0x1110fee0>"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from pyecharts.charts import Gauge\n",
    "Gauge().load_javascript() #在Jupyterlab中制图前需加载一次JavaScript函数！！"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<!DOCTYPE html>\n",
       "<html>\n",
       "<head>\n",
       "    <meta charset=\"UTF-8\">\n",
       "</head>\n",
       "<body>\n",
       "        <div id=\"0f147b0fdf3640ce8f60025bd61b5ee3\" class=\"chart-container\" style=\"width:560px; height:380px;\"></div>\n",
       "    <script>\n",
       "        var chart_0f147b0fdf3640ce8f60025bd61b5ee3 = echarts.init(\n",
       "            document.getElementById('0f147b0fdf3640ce8f60025bd61b5ee3'), 'white', {renderer: 'canvas'});\n",
       "        var option_0f147b0fdf3640ce8f60025bd61b5ee3 = {\n",
       "    \"backgroundColor\": \"white\",\n",
       "    \"animation\": true,\n",
       "    \"animationThreshold\": 2000,\n",
       "    \"animationDuration\": 1000,\n",
       "    \"animationEasing\": \"cubicOut\",\n",
       "    \"animationDelay\": 0,\n",
       "    \"animationDurationUpdate\": 300,\n",
       "    \"animationEasingUpdate\": \"cubicOut\",\n",
       "    \"animationDelayUpdate\": 0,\n",
       "    \"color\": [\n",
       "        \"#c23531\",\n",
       "        \"#2f4554\",\n",
       "        \"#61a0a8\",\n",
       "        \"#d48265\",\n",
       "        \"#749f83\",\n",
       "        \"#ca8622\",\n",
       "        \"#bda29a\",\n",
       "        \"#6e7074\",\n",
       "        \"#546570\",\n",
       "        \"#c4ccd3\",\n",
       "        \"#f05b72\",\n",
       "        \"#ef5b9c\",\n",
       "        \"#f47920\",\n",
       "        \"#905a3d\",\n",
       "        \"#fab27b\",\n",
       "        \"#2a5caa\",\n",
       "        \"#444693\",\n",
       "        \"#726930\",\n",
       "        \"#b2d235\",\n",
       "        \"#6d8346\",\n",
       "        \"#ac6767\",\n",
       "        \"#1d953f\",\n",
       "        \"#6950a1\",\n",
       "        \"#918597\"\n",
       "    ],\n",
       "    \"series\": [\n",
       "        {\n",
       "            \"type\": \"gauge\",\n",
       "            \"title\": {\n",
       "                \"show\": true,\n",
       "                \"offsetCenter\": [\n",
       "                    0,\n",
       "                    \"-40%\"\n",
       "                ],\n",
       "                \"color\": \"#333\",\n",
       "                \"fontStyle\": \"normal\",\n",
       "                \"fontWeight\": \"normal\",\n",
       "                \"fontFamily\": \"sans-serif\",\n",
       "                \"fontSize\": 15,\n",
       "                \"backgroundColor\": \"transparent\",\n",
       "                \"borderColor\": \"transparent\",\n",
       "                \"borderWidth\": 0,\n",
       "                \"borderRadius\": 0,\n",
       "                \"padding\": 0,\n",
       "                \"shadowColor\": \"transparent\",\n",
       "                \"shadowBlur\": 0,\n",
       "                \"shadowOffsetX\": 0,\n",
       "                \"shadowOffsetY\": 0\n",
       "            },\n",
       "            \"detail\": {\n",
       "                \"show\": true,\n",
       "                \"backgroundColor\": \"transparent\",\n",
       "                \"borderWidth\": 0,\n",
       "                \"borderColor\": \"transparent\",\n",
       "                \"offsetCenter\": [\n",
       "                    0,\n",
       "                    \"-40%\"\n",
       "                ],\n",
       "                \"formatter\": \"{value}%\",\n",
       "                \"color\": \"auto\",\n",
       "                \"fontStyle\": \"normal\",\n",
       "                \"fontWeight\": \"normal\",\n",
       "                \"fontFamily\": \"sans-serif\",\n",
       "                \"fontSize\": 15,\n",
       "                \"borderRadius\": 0,\n",
       "                \"padding\": 0,\n",
       "                \"shadowColor\": \"transparent\",\n",
       "                \"shadowBlur\": 0,\n",
       "                \"shadowOffsetX\": 0,\n",
       "                \"shadowOffsetY\": 0\n",
       "            },\n",
       "            \"min\": 0,\n",
       "            \"max\": 100,\n",
       "            \"splitNumber\": 10,\n",
       "            \"radius\": \"75%\",\n",
       "            \"startAngle\": 225,\n",
       "            \"endAngle\": -45,\n",
       "            \"clockwise\": true,\n",
       "            \"data\": [\n",
       "                {\n",
       "                    \"name\": \"\\u5b8c\\u6210\\u7387\",\n",
       "                    \"value\": 90\n",
       "                }\n",
       "            ],\n",
       "            \"pointer\": {\n",
       "                \"show\": true,\n",
       "                \"length\": \"80%\",\n",
       "                \"width\": 8\n",
       "            }\n",
       "        }\n",
       "    ],\n",
       "    \"legend\": [\n",
       "        {\n",
       "            \"data\": [\n",
       "                \"\"\n",
       "            ],\n",
       "            \"selected\": {\n",
       "                \"\": true\n",
       "            }\n",
       "        }\n",
       "    ],\n",
       "    \"tooltip\": {\n",
       "        \"show\": true,\n",
       "        \"trigger\": \"item\",\n",
       "        \"triggerOn\": \"mousemove|click\",\n",
       "        \"axisPointer\": {\n",
       "            \"type\": \"line\"\n",
       "        },\n",
       "        \"showContent\": true,\n",
       "        \"alwaysShowContent\": false,\n",
       "        \"showDelay\": 0,\n",
       "        \"hideDelay\": 100,\n",
       "        \"textStyle\": {\n",
       "            \"fontSize\": 14\n",
       "        },\n",
       "        \"borderWidth\": 0,\n",
       "        \"padding\": 5\n",
       "    }\n",
       "};\n",
       "        chart_0f147b0fdf3640ce8f60025bd61b5ee3.setOption(option_0f147b0fdf3640ce8f60025bd61b5ee3);\n",
       "    </script>\n",
       "</body>\n",
       "</html>\n"
      ],
      "text/plain": [
       "<pyecharts.render.display.HTML at 0x10ba1880>"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Gauge().add(\"\",[(\"完成率\", 66.6)]).render_notebook()\n",
    "Gauge(figsize).add(\"\",[(\"完成率\", 90)]).render_notebook()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "#### 5.4.2.2 条图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "#基本的pyecharts绘图是基于列表数据的\n",
    "X=['A','B','C','D','E','F','G']\n",
    "Y=[1,4,7,3,2,5,6]\n",
    "Z=[6,5,3,2,7,4,1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<!DOCTYPE html>\n",
       "<html>\n",
       "<head>\n",
       "    <meta charset=\"UTF-8\">\n",
       "</head>\n",
       "<body>\n",
       "        <div id=\"c8c0a294d15146eaacbc7841b5e54541\" class=\"chart-container\" style=\"width:560px; height:380px;\"></div>\n",
       "    <script>\n",
       "        var chart_c8c0a294d15146eaacbc7841b5e54541 = echarts.init(\n",
       "            document.getElementById('c8c0a294d15146eaacbc7841b5e54541'), 'white', {renderer: 'canvas'});\n",
       "        var option_c8c0a294d15146eaacbc7841b5e54541 = {\n",
       "    \"backgroundColor\": \"white\",\n",
       "    \"animation\": true,\n",
       "    \"animationThreshold\": 2000,\n",
       "    \"animationDuration\": 1000,\n",
       "    \"animationEasing\": \"cubicOut\",\n",
       "    \"animationDelay\": 0,\n",
       "    \"animationDurationUpdate\": 300,\n",
       "    \"animationEasingUpdate\": \"cubicOut\",\n",
       "    \"animationDelayUpdate\": 0,\n",
       "    \"color\": [\n",
       "        \"#c23531\",\n",
       "        \"#2f4554\",\n",
       "        \"#61a0a8\",\n",
       "        \"#d48265\",\n",
       "        \"#749f83\",\n",
       "        \"#ca8622\",\n",
       "        \"#bda29a\",\n",
       "        \"#6e7074\",\n",
       "        \"#546570\",\n",
       "        \"#c4ccd3\",\n",
       "        \"#f05b72\",\n",
       "        \"#ef5b9c\",\n",
       "        \"#f47920\",\n",
       "        \"#905a3d\",\n",
       "        \"#fab27b\",\n",
       "        \"#2a5caa\",\n",
       "        \"#444693\",\n",
       "        \"#726930\",\n",
       "        \"#b2d235\",\n",
       "        \"#6d8346\",\n",
       "        \"#ac6767\",\n",
       "        \"#1d953f\",\n",
       "        \"#6950a1\",\n",
       "        \"#918597\"\n",
       "    ],\n",
       "    \"series\": [\n",
       "        {\n",
       "            \"type\": \"bar\",\n",
       "            \"name\": \"\\u5782\\u76f4\\u6761\\u56fe\",\n",
       "            \"legendHoverLink\": true,\n",
       "            \"data\": [\n",
       "                1,\n",
       "                4,\n",
       "                7,\n",
       "                3,\n",
       "                2,\n",
       "                5,\n",
       "                6\n",
       "            ],\n",
       "            \"showBackground\": false,\n",
       "            \"barMinHeight\": 0,\n",
       "            \"barCategoryGap\": \"20%\",\n",
       "            \"barGap\": \"30%\",\n",
       "            \"large\": false,\n",
       "            \"largeThreshold\": 400,\n",
       "            \"seriesLayoutBy\": \"column\",\n",
       "            \"datasetIndex\": 0,\n",
       "            \"clip\": true,\n",
       "            \"zlevel\": 0,\n",
       "            \"z\": 2,\n",
       "            \"label\": {\n",
       "                \"show\": true,\n",
       "                \"position\": \"top\",\n",
       "                \"margin\": 8\n",
       "            }\n",
       "        }\n",
       "    ],\n",
       "    \"legend\": [\n",
       "        {\n",
       "            \"data\": [\n",
       "                \"\\u5782\\u76f4\\u6761\\u56fe\"\n",
       "            ],\n",
       "            \"selected\": {\n",
       "                \"\\u5782\\u76f4\\u6761\\u56fe\": true\n",
       "            }\n",
       "        }\n",
       "    ],\n",
       "    \"tooltip\": {\n",
       "        \"show\": true,\n",
       "        \"trigger\": \"item\",\n",
       "        \"triggerOn\": \"mousemove|click\",\n",
       "        \"axisPointer\": {\n",
       "            \"type\": \"line\"\n",
       "        },\n",
       "        \"showContent\": true,\n",
       "        \"alwaysShowContent\": false,\n",
       "        \"showDelay\": 0,\n",
       "        \"hideDelay\": 100,\n",
       "        \"textStyle\": {\n",
       "            \"fontSize\": 14\n",
       "        },\n",
       "        \"borderWidth\": 0,\n",
       "        \"padding\": 5\n",
       "    },\n",
       "    \"xAxis\": [\n",
       "        {\n",
       "            \"show\": true,\n",
       "            \"scale\": false,\n",
       "            \"nameLocation\": \"end\",\n",
       "            \"nameGap\": 15,\n",
       "            \"gridIndex\": 0,\n",
       "            \"inverse\": false,\n",
       "            \"offset\": 0,\n",
       "            \"splitNumber\": 5,\n",
       "            \"minInterval\": 0,\n",
       "            \"splitLine\": {\n",
       "                \"show\": false,\n",
       "                \"lineStyle\": {\n",
       "                    \"show\": true,\n",
       "                    \"width\": 1,\n",
       "                    \"opacity\": 1,\n",
       "                    \"curveness\": 0,\n",
       "                    \"type\": \"solid\"\n",
       "                }\n",
       "            },\n",
       "            \"data\": [\n",
       "                \"A\",\n",
       "                \"B\",\n",
       "                \"C\",\n",
       "                \"D\",\n",
       "                \"E\",\n",
       "                \"F\",\n",
       "                \"G\"\n",
       "            ]\n",
       "        }\n",
       "    ],\n",
       "    \"yAxis\": [\n",
       "        {\n",
       "            \"show\": true,\n",
       "            \"scale\": false,\n",
       "            \"nameLocation\": \"end\",\n",
       "            \"nameGap\": 15,\n",
       "            \"gridIndex\": 0,\n",
       "            \"inverse\": false,\n",
       "            \"offset\": 0,\n",
       "            \"splitNumber\": 5,\n",
       "            \"minInterval\": 0,\n",
       "            \"splitLine\": {\n",
       "                \"show\": false,\n",
       "                \"lineStyle\": {\n",
       "                    \"show\": true,\n",
       "                    \"width\": 1,\n",
       "                    \"opacity\": 1,\n",
       "                    \"curveness\": 0,\n",
       "                    \"type\": \"solid\"\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    ]\n",
       "};\n",
       "        chart_c8c0a294d15146eaacbc7841b5e54541.setOption(option_c8c0a294d15146eaacbc7841b5e54541);\n",
       "    </script>\n",
       "</body>\n",
       "</html>\n"
      ],
      "text/plain": [
       "<pyecharts.render.display.HTML at 0x127c4c70>"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from pyecharts.charts import Bar          #加载pyecharts绘制条图(Bar)函数\n",
    "bar1=Bar(figsize)                         #初始化条图\n",
    "bar1.add_xaxis(X).add_yaxis(\"垂直条图\",Y)   \n",
    "bar1.render_notebook()  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<!DOCTYPE html>\n",
       "<html>\n",
       "<head>\n",
       "    <meta charset=\"UTF-8\">\n",
       "</head>\n",
       "<body>\n",
       "        <div id=\"46754134875e44beb57e1dfcc5ccb0fa\" class=\"chart-container\" style=\"width:560px; height:380px;\"></div>\n",
       "    <script>\n",
       "        var chart_46754134875e44beb57e1dfcc5ccb0fa = echarts.init(\n",
       "            document.getElementById('46754134875e44beb57e1dfcc5ccb0fa'), 'white', {renderer: 'canvas'});\n",
       "        var option_46754134875e44beb57e1dfcc5ccb0fa = {\n",
       "    \"backgroundColor\": \"white\",\n",
       "    \"animation\": true,\n",
       "    \"animationThreshold\": 2000,\n",
       "    \"animationDuration\": 1000,\n",
       "    \"animationEasing\": \"cubicOut\",\n",
       "    \"animationDelay\": 0,\n",
       "    \"animationDurationUpdate\": 300,\n",
       "    \"animationEasingUpdate\": \"cubicOut\",\n",
       "    \"animationDelayUpdate\": 0,\n",
       "    \"color\": [\n",
       "        \"#c23531\",\n",
       "        \"#2f4554\",\n",
       "        \"#61a0a8\",\n",
       "        \"#d48265\",\n",
       "        \"#749f83\",\n",
       "        \"#ca8622\",\n",
       "        \"#bda29a\",\n",
       "        \"#6e7074\",\n",
       "        \"#546570\",\n",
       "        \"#c4ccd3\",\n",
       "        \"#f05b72\",\n",
       "        \"#ef5b9c\",\n",
       "        \"#f47920\",\n",
       "        \"#905a3d\",\n",
       "        \"#fab27b\",\n",
       "        \"#2a5caa\",\n",
       "        \"#444693\",\n",
       "        \"#726930\",\n",
       "        \"#b2d235\",\n",
       "        \"#6d8346\",\n",
       "        \"#ac6767\",\n",
       "        \"#1d953f\",\n",
       "        \"#6950a1\",\n",
       "        \"#918597\"\n",
       "    ],\n",
       "    \"series\": [\n",
       "        {\n",
       "            \"type\": \"bar\",\n",
       "            \"legendHoverLink\": true,\n",
       "            \"data\": [\n",
       "                1,\n",
       "                4,\n",
       "                7,\n",
       "                3,\n",
       "                2,\n",
       "                5,\n",
       "                6\n",
       "            ],\n",
       "            \"showBackground\": false,\n",
       "            \"barMinHeight\": 0,\n",
       "            \"barCategoryGap\": \"20%\",\n",
       "            \"barGap\": \"30%\",\n",
       "            \"large\": false,\n",
       "            \"largeThreshold\": 400,\n",
       "            \"seriesLayoutBy\": \"column\",\n",
       "            \"datasetIndex\": 0,\n",
       "            \"clip\": true,\n",
       "            \"zlevel\": 0,\n",
       "            \"z\": 2,\n",
       "            \"label\": {\n",
       "                \"show\": true,\n",
       "                \"position\": \"top\",\n",
       "                \"margin\": 8\n",
       "            }\n",
       "        }\n",
       "    ],\n",
       "    \"legend\": [\n",
       "        {\n",
       "            \"data\": [\n",
       "                \"\"\n",
       "            ],\n",
       "            \"selected\": {\n",
       "                \"\": true\n",
       "            }\n",
       "        }\n",
       "    ],\n",
       "    \"tooltip\": {\n",
       "        \"show\": true,\n",
       "        \"trigger\": \"item\",\n",
       "        \"triggerOn\": \"mousemove|click\",\n",
       "        \"axisPointer\": {\n",
       "            \"type\": \"line\"\n",
       "        },\n",
       "        \"showContent\": true,\n",
       "        \"alwaysShowContent\": false,\n",
       "        \"showDelay\": 0,\n",
       "        \"hideDelay\": 100,\n",
       "        \"textStyle\": {\n",
       "            \"fontSize\": 14\n",
       "        },\n",
       "        \"borderWidth\": 0,\n",
       "        \"padding\": 5\n",
       "    },\n",
       "    \"xAxis\": [\n",
       "        {\n",
       "            \"show\": true,\n",
       "            \"scale\": false,\n",
       "            \"nameLocation\": \"end\",\n",
       "            \"nameGap\": 15,\n",
       "            \"gridIndex\": 0,\n",
       "            \"inverse\": false,\n",
       "            \"offset\": 0,\n",
       "            \"splitNumber\": 5,\n",
       "            \"minInterval\": 0,\n",
       "            \"splitLine\": {\n",
       "                \"show\": false,\n",
       "                \"lineStyle\": {\n",
       "                    \"show\": true,\n",
       "                    \"width\": 1,\n",
       "                    \"opacity\": 1,\n",
       "                    \"curveness\": 0,\n",
       "                    \"type\": \"solid\"\n",
       "                }\n",
       "            },\n",
       "            \"data\": [\n",
       "                \"A\",\n",
       "                \"B\",\n",
       "                \"C\",\n",
       "                \"D\",\n",
       "                \"E\",\n",
       "                \"F\",\n",
       "                \"G\"\n",
       "            ]\n",
       "        }\n",
       "    ],\n",
       "    \"yAxis\": [\n",
       "        {\n",
       "            \"show\": true,\n",
       "            \"scale\": false,\n",
       "            \"nameLocation\": \"end\",\n",
       "            \"nameGap\": 15,\n",
       "            \"gridIndex\": 0,\n",
       "            \"inverse\": false,\n",
       "            \"offset\": 0,\n",
       "            \"splitNumber\": 5,\n",
       "            \"minInterval\": 0,\n",
       "            \"splitLine\": {\n",
       "                \"show\": false,\n",
       "                \"lineStyle\": {\n",
       "                    \"show\": true,\n",
       "                    \"width\": 1,\n",
       "                    \"opacity\": 1,\n",
       "                    \"curveness\": 0,\n",
       "                    \"type\": \"solid\"\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    ]\n",
       "};\n",
       "        chart_46754134875e44beb57e1dfcc5ccb0fa.setOption(option_46754134875e44beb57e1dfcc5ccb0fa);\n",
       "    </script>\n",
       "</body>\n",
       "</html>\n"
      ],
      "text/plain": [
       "<pyecharts.render.display.HTML at 0x127c4160>"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Bar(figsize).add_xaxis(X).add_yaxis(\"\",Y).render_notebook()  #链式写法"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<!DOCTYPE html>\n",
       "<html>\n",
       "<head>\n",
       "    <meta charset=\"UTF-8\">\n",
       "</head>\n",
       "<body>\n",
       "        <div id=\"7a76755de56c49a9b4e90bb5f7703258\" class=\"chart-container\" style=\"width:560px; height:380px;\"></div>\n",
       "    <script>\n",
       "        var chart_7a76755de56c49a9b4e90bb5f7703258 = echarts.init(\n",
       "            document.getElementById('7a76755de56c49a9b4e90bb5f7703258'), 'white', {renderer: 'canvas'});\n",
       "        var option_7a76755de56c49a9b4e90bb5f7703258 = {\n",
       "    \"backgroundColor\": \"white\",\n",
       "    \"animation\": true,\n",
       "    \"animationThreshold\": 2000,\n",
       "    \"animationDuration\": 1000,\n",
       "    \"animationEasing\": \"cubicOut\",\n",
       "    \"animationDelay\": 0,\n",
       "    \"animationDurationUpdate\": 300,\n",
       "    \"animationEasingUpdate\": \"cubicOut\",\n",
       "    \"animationDelayUpdate\": 0,\n",
       "    \"color\": [\n",
       "        \"#c23531\",\n",
       "        \"#2f4554\",\n",
       "        \"#61a0a8\",\n",
       "        \"#d48265\",\n",
       "        \"#749f83\",\n",
       "        \"#ca8622\",\n",
       "        \"#bda29a\",\n",
       "        \"#6e7074\",\n",
       "        \"#546570\",\n",
       "        \"#c4ccd3\",\n",
       "        \"#f05b72\",\n",
       "        \"#ef5b9c\",\n",
       "        \"#f47920\",\n",
       "        \"#905a3d\",\n",
       "        \"#fab27b\",\n",
       "        \"#2a5caa\",\n",
       "        \"#444693\",\n",
       "        \"#726930\",\n",
       "        \"#b2d235\",\n",
       "        \"#6d8346\",\n",
       "        \"#ac6767\",\n",
       "        \"#1d953f\",\n",
       "        \"#6950a1\",\n",
       "        \"#918597\"\n",
       "    ],\n",
       "    \"series\": [\n",
       "        {\n",
       "            \"type\": \"bar\",\n",
       "            \"name\": \"\\u6c34\\u5e73\\u6761\\u56fe\",\n",
       "            \"legendHoverLink\": true,\n",
       "            \"data\": [\n",
       "                1,\n",
       "                4,\n",
       "                7,\n",
       "                3,\n",
       "                2,\n",
       "                5,\n",
       "                6\n",
       "            ],\n",
       "            \"showBackground\": false,\n",
       "            \"barMinHeight\": 0,\n",
       "            \"barCategoryGap\": \"20%\",\n",
       "            \"barGap\": \"30%\",\n",
       "            \"large\": false,\n",
       "            \"largeThreshold\": 400,\n",
       "            \"seriesLayoutBy\": \"column\",\n",
       "            \"datasetIndex\": 0,\n",
       "            \"clip\": true,\n",
       "            \"zlevel\": 0,\n",
       "            \"z\": 2,\n",
       "            \"label\": {\n",
       "                \"show\": true,\n",
       "                \"position\": \"top\",\n",
       "                \"margin\": 8\n",
       "            }\n",
       "        }\n",
       "    ],\n",
       "    \"legend\": [\n",
       "        {\n",
       "            \"data\": [\n",
       "                \"\\u6c34\\u5e73\\u6761\\u56fe\"\n",
       "            ],\n",
       "            \"selected\": {\n",
       "                \"\\u6c34\\u5e73\\u6761\\u56fe\": true\n",
       "            }\n",
       "        }\n",
       "    ],\n",
       "    \"tooltip\": {\n",
       "        \"show\": true,\n",
       "        \"trigger\": \"item\",\n",
       "        \"triggerOn\": \"mousemove|click\",\n",
       "        \"axisPointer\": {\n",
       "            \"type\": \"line\"\n",
       "        },\n",
       "        \"showContent\": true,\n",
       "        \"alwaysShowContent\": false,\n",
       "        \"showDelay\": 0,\n",
       "        \"hideDelay\": 100,\n",
       "        \"textStyle\": {\n",
       "            \"fontSize\": 14\n",
       "        },\n",
       "        \"borderWidth\": 0,\n",
       "        \"padding\": 5\n",
       "    },\n",
       "    \"xAxis\": [\n",
       "        {\n",
       "            \"show\": true,\n",
       "            \"scale\": false,\n",
       "            \"nameLocation\": \"end\",\n",
       "            \"nameGap\": 15,\n",
       "            \"gridIndex\": 0,\n",
       "            \"inverse\": false,\n",
       "            \"offset\": 0,\n",
       "            \"splitNumber\": 5,\n",
       "            \"minInterval\": 0,\n",
       "            \"splitLine\": {\n",
       "                \"show\": false,\n",
       "                \"lineStyle\": {\n",
       "                    \"show\": true,\n",
       "                    \"width\": 1,\n",
       "                    \"opacity\": 1,\n",
       "                    \"curveness\": 0,\n",
       "                    \"type\": \"solid\"\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    ],\n",
       "    \"yAxis\": [\n",
       "        {\n",
       "            \"show\": true,\n",
       "            \"scale\": false,\n",
       "            \"nameLocation\": \"end\",\n",
       "            \"nameGap\": 15,\n",
       "            \"gridIndex\": 0,\n",
       "            \"inverse\": false,\n",
       "            \"offset\": 0,\n",
       "            \"splitNumber\": 5,\n",
       "            \"minInterval\": 0,\n",
       "            \"splitLine\": {\n",
       "                \"show\": false,\n",
       "                \"lineStyle\": {\n",
       "                    \"show\": true,\n",
       "                    \"width\": 1,\n",
       "                    \"opacity\": 1,\n",
       "                    \"curveness\": 0,\n",
       "                    \"type\": \"solid\"\n",
       "                }\n",
       "            },\n",
       "            \"data\": [\n",
       "                \"A\",\n",
       "                \"B\",\n",
       "                \"C\",\n",
       "                \"D\",\n",
       "                \"E\",\n",
       "                \"F\",\n",
       "                \"G\"\n",
       "            ]\n",
       "        }\n",
       "    ]\n",
       "};\n",
       "        chart_7a76755de56c49a9b4e90bb5f7703258.setOption(option_7a76755de56c49a9b4e90bb5f7703258);\n",
       "    </script>\n",
       "</body>\n",
       "</html>\n"
      ],
      "text/plain": [
       "<pyecharts.render.display.HTML at 0x127a0280>"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bar2=Bar(figsize) \n",
    "bar2.add_xaxis(X).add_yaxis(\"水平条图\",Y).reversal_axis()     \n",
    "bar2.render_notebook()  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<!DOCTYPE html>\n",
       "<html>\n",
       "<head>\n",
       "    <meta charset=\"UTF-8\">\n",
       "</head>\n",
       "<body>\n",
       "        <div id=\"0c7a6ab65b0d4a839c802a244d85acf0\" class=\"chart-container\" style=\"width:560px; height:380px;\"></div>\n",
       "    <script>\n",
       "        var chart_0c7a6ab65b0d4a839c802a244d85acf0 = echarts.init(\n",
       "            document.getElementById('0c7a6ab65b0d4a839c802a244d85acf0'), 'white', {renderer: 'canvas'});\n",
       "        var option_0c7a6ab65b0d4a839c802a244d85acf0 = {\n",
       "    \"backgroundColor\": \"white\",\n",
       "    \"animation\": true,\n",
       "    \"animationThreshold\": 2000,\n",
       "    \"animationDuration\": 1000,\n",
       "    \"animationEasing\": \"cubicOut\",\n",
       "    \"animationDelay\": 0,\n",
       "    \"animationDurationUpdate\": 300,\n",
       "    \"animationEasingUpdate\": \"cubicOut\",\n",
       "    \"animationDelayUpdate\": 0,\n",
       "    \"color\": [\n",
       "        \"#c23531\",\n",
       "        \"#2f4554\",\n",
       "        \"#61a0a8\",\n",
       "        \"#d48265\",\n",
       "        \"#749f83\",\n",
       "        \"#ca8622\",\n",
       "        \"#bda29a\",\n",
       "        \"#6e7074\",\n",
       "        \"#546570\",\n",
       "        \"#c4ccd3\",\n",
       "        \"#f05b72\",\n",
       "        \"#ef5b9c\",\n",
       "        \"#f47920\",\n",
       "        \"#905a3d\",\n",
       "        \"#fab27b\",\n",
       "        \"#2a5caa\",\n",
       "        \"#444693\",\n",
       "        \"#726930\",\n",
       "        \"#b2d235\",\n",
       "        \"#6d8346\",\n",
       "        \"#ac6767\",\n",
       "        \"#1d953f\",\n",
       "        \"#6950a1\",\n",
       "        \"#918597\"\n",
       "    ],\n",
       "    \"series\": [\n",
       "        {\n",
       "            \"type\": \"bar\",\n",
       "            \"name\": \"\\u67611\",\n",
       "            \"legendHoverLink\": true,\n",
       "            \"data\": [\n",
       "                1,\n",
       "                4,\n",
       "                7,\n",
       "                3,\n",
       "                2,\n",
       "                5,\n",
       "                6\n",
       "            ],\n",
       "            \"showBackground\": false,\n",
       "            \"barMinHeight\": 0,\n",
       "            \"barCategoryGap\": \"20%\",\n",
       "            \"barGap\": \"30%\",\n",
       "            \"large\": false,\n",
       "            \"largeThreshold\": 400,\n",
       "            \"seriesLayoutBy\": \"column\",\n",
       "            \"datasetIndex\": 0,\n",
       "            \"clip\": true,\n",
       "            \"zlevel\": 0,\n",
       "            \"z\": 2,\n",
       "            \"label\": {\n",
       "                \"show\": true,\n",
       "                \"position\": \"top\",\n",
       "                \"margin\": 8\n",
       "            }\n",
       "        },\n",
       "        {\n",
       "            \"type\": \"bar\",\n",
       "            \"name\": \"\\u67612\",\n",
       "            \"legendHoverLink\": true,\n",
       "            \"data\": [\n",
       "                6,\n",
       "                5,\n",
       "                3,\n",
       "                2,\n",
       "                7,\n",
       "                4,\n",
       "                1\n",
       "            ],\n",
       "            \"showBackground\": false,\n",
       "            \"barMinHeight\": 0,\n",
       "            \"barCategoryGap\": \"20%\",\n",
       "            \"barGap\": \"30%\",\n",
       "            \"large\": false,\n",
       "            \"largeThreshold\": 400,\n",
       "            \"seriesLayoutBy\": \"column\",\n",
       "            \"datasetIndex\": 0,\n",
       "            \"clip\": true,\n",
       "            \"zlevel\": 0,\n",
       "            \"z\": 2,\n",
       "            \"label\": {\n",
       "                \"show\": true,\n",
       "                \"position\": \"top\",\n",
       "                \"margin\": 8\n",
       "            }\n",
       "        }\n",
       "    ],\n",
       "    \"legend\": [\n",
       "        {\n",
       "            \"data\": [\n",
       "                \"\\u67611\",\n",
       "                \"\\u67612\"\n",
       "            ],\n",
       "            \"selected\": {\n",
       "                \"\\u67611\": true,\n",
       "                \"\\u67612\": true\n",
       "            }\n",
       "        }\n",
       "    ],\n",
       "    \"tooltip\": {\n",
       "        \"show\": true,\n",
       "        \"trigger\": \"item\",\n",
       "        \"triggerOn\": \"mousemove|click\",\n",
       "        \"axisPointer\": {\n",
       "            \"type\": \"line\"\n",
       "        },\n",
       "        \"showContent\": true,\n",
       "        \"alwaysShowContent\": false,\n",
       "        \"showDelay\": 0,\n",
       "        \"hideDelay\": 100,\n",
       "        \"textStyle\": {\n",
       "            \"fontSize\": 14\n",
       "        },\n",
       "        \"borderWidth\": 0,\n",
       "        \"padding\": 5\n",
       "    },\n",
       "    \"xAxis\": [\n",
       "        {\n",
       "            \"show\": true,\n",
       "            \"scale\": false,\n",
       "            \"nameLocation\": \"end\",\n",
       "            \"nameGap\": 15,\n",
       "            \"gridIndex\": 0,\n",
       "            \"inverse\": false,\n",
       "            \"offset\": 0,\n",
       "            \"splitNumber\": 5,\n",
       "            \"minInterval\": 0,\n",
       "            \"splitLine\": {\n",
       "                \"show\": false,\n",
       "                \"lineStyle\": {\n",
       "                    \"show\": true,\n",
       "                    \"width\": 1,\n",
       "                    \"opacity\": 1,\n",
       "                    \"curveness\": 0,\n",
       "                    \"type\": \"solid\"\n",
       "                }\n",
       "            },\n",
       "            \"data\": [\n",
       "                \"A\",\n",
       "                \"B\",\n",
       "                \"C\",\n",
       "                \"D\",\n",
       "                \"E\",\n",
       "                \"F\",\n",
       "                \"G\"\n",
       "            ]\n",
       "        }\n",
       "    ],\n",
       "    \"yAxis\": [\n",
       "        {\n",
       "            \"show\": true,\n",
       "            \"scale\": false,\n",
       "            \"nameLocation\": \"end\",\n",
       "            \"nameGap\": 15,\n",
       "            \"gridIndex\": 0,\n",
       "            \"inverse\": false,\n",
       "            \"offset\": 0,\n",
       "            \"splitNumber\": 5,\n",
       "            \"minInterval\": 0,\n",
       "            \"splitLine\": {\n",
       "                \"show\": false,\n",
       "                \"lineStyle\": {\n",
       "                    \"show\": true,\n",
       "                    \"width\": 1,\n",
       "                    \"opacity\": 1,\n",
       "                    \"curveness\": 0,\n",
       "                    \"type\": \"solid\"\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    ]\n",
       "};\n",
       "        chart_0c7a6ab65b0d4a839c802a244d85acf0.setOption(option_0c7a6ab65b0d4a839c802a244d85acf0);\n",
       "    </script>\n",
       "</body>\n",
       "</html>\n"
      ],
      "text/plain": [
       "<pyecharts.render.display.HTML at 0x127c4670>"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bar3=Bar(figsize)\n",
    "bar3.add_xaxis(X).add_yaxis(\"条1\",Y).add_yaxis(\"条2\",Z) #复试条图\n",
    "bar3.render_notebook()  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<!DOCTYPE html>\n",
       "<html>\n",
       "<head>\n",
       "    <meta charset=\"UTF-8\">\n",
       "</head>\n",
       "<body>\n",
       "        <div id=\"c53fedcd4b614331884f4144dddd9eff\" class=\"chart-container\" style=\"width:560px; height:380px;\"></div>\n",
       "    <script>\n",
       "        var chart_c53fedcd4b614331884f4144dddd9eff = echarts.init(\n",
       "            document.getElementById('c53fedcd4b614331884f4144dddd9eff'), 'white', {renderer: 'canvas'});\n",
       "        var option_c53fedcd4b614331884f4144dddd9eff = {\n",
       "    \"backgroundColor\": \"white\",\n",
       "    \"animation\": true,\n",
       "    \"animationThreshold\": 2000,\n",
       "    \"animationDuration\": 1000,\n",
       "    \"animationEasing\": \"cubicOut\",\n",
       "    \"animationDelay\": 0,\n",
       "    \"animationDurationUpdate\": 300,\n",
       "    \"animationEasingUpdate\": \"cubicOut\",\n",
       "    \"animationDelayUpdate\": 0,\n",
       "    \"color\": [\n",
       "        \"#c23531\",\n",
       "        \"#2f4554\",\n",
       "        \"#61a0a8\",\n",
       "        \"#d48265\",\n",
       "        \"#749f83\",\n",
       "        \"#ca8622\",\n",
       "        \"#bda29a\",\n",
       "        \"#6e7074\",\n",
       "        \"#546570\",\n",
       "        \"#c4ccd3\",\n",
       "        \"#f05b72\",\n",
       "        \"#ef5b9c\",\n",
       "        \"#f47920\",\n",
       "        \"#905a3d\",\n",
       "        \"#fab27b\",\n",
       "        \"#2a5caa\",\n",
       "        \"#444693\",\n",
       "        \"#726930\",\n",
       "        \"#b2d235\",\n",
       "        \"#6d8346\",\n",
       "        \"#ac6767\",\n",
       "        \"#1d953f\",\n",
       "        \"#6950a1\",\n",
       "        \"#918597\"\n",
       "    ],\n",
       "    \"series\": [\n",
       "        {\n",
       "            \"type\": \"bar\",\n",
       "            \"name\": \"\\u67611\",\n",
       "            \"legendHoverLink\": true,\n",
       "            \"data\": [\n",
       "                1,\n",
       "                4,\n",
       "                7,\n",
       "                3,\n",
       "                2,\n",
       "                5,\n",
       "                6\n",
       "            ],\n",
       "            \"showBackground\": false,\n",
       "            \"stack\": \"stack1\",\n",
       "            \"barMinHeight\": 0,\n",
       "            \"barCategoryGap\": \"20%\",\n",
       "            \"barGap\": \"30%\",\n",
       "            \"large\": false,\n",
       "            \"largeThreshold\": 400,\n",
       "            \"seriesLayoutBy\": \"column\",\n",
       "            \"datasetIndex\": 0,\n",
       "            \"clip\": true,\n",
       "            \"zlevel\": 0,\n",
       "            \"z\": 2,\n",
       "            \"label\": {\n",
       "                \"show\": true,\n",
       "                \"position\": \"top\",\n",
       "                \"margin\": 8\n",
       "            }\n",
       "        },\n",
       "        {\n",
       "            \"type\": \"bar\",\n",
       "            \"name\": \"\\u67612\",\n",
       "            \"legendHoverLink\": true,\n",
       "            \"data\": [\n",
       "                6,\n",
       "                5,\n",
       "                3,\n",
       "                2,\n",
       "                7,\n",
       "                4,\n",
       "                1\n",
       "            ],\n",
       "            \"showBackground\": false,\n",
       "            \"stack\": \"stack1\",\n",
       "            \"barMinHeight\": 0,\n",
       "            \"barCategoryGap\": \"20%\",\n",
       "            \"barGap\": \"30%\",\n",
       "            \"large\": false,\n",
       "            \"largeThreshold\": 400,\n",
       "            \"seriesLayoutBy\": \"column\",\n",
       "            \"datasetIndex\": 0,\n",
       "            \"clip\": true,\n",
       "            \"zlevel\": 0,\n",
       "            \"z\": 2,\n",
       "            \"label\": {\n",
       "                \"show\": true,\n",
       "                \"position\": \"top\",\n",
       "                \"margin\": 8\n",
       "            }\n",
       "        }\n",
       "    ],\n",
       "    \"legend\": [\n",
       "        {\n",
       "            \"data\": [\n",
       "                \"\\u67611\",\n",
       "                \"\\u67612\"\n",
       "            ],\n",
       "            \"selected\": {\n",
       "                \"\\u67611\": true,\n",
       "                \"\\u67612\": true\n",
       "            }\n",
       "        }\n",
       "    ],\n",
       "    \"tooltip\": {\n",
       "        \"show\": true,\n",
       "        \"trigger\": \"item\",\n",
       "        \"triggerOn\": \"mousemove|click\",\n",
       "        \"axisPointer\": {\n",
       "            \"type\": \"line\"\n",
       "        },\n",
       "        \"showContent\": true,\n",
       "        \"alwaysShowContent\": false,\n",
       "        \"showDelay\": 0,\n",
       "        \"hideDelay\": 100,\n",
       "        \"textStyle\": {\n",
       "            \"fontSize\": 14\n",
       "        },\n",
       "        \"borderWidth\": 0,\n",
       "        \"padding\": 5\n",
       "    },\n",
       "    \"xAxis\": [\n",
       "        {\n",
       "            \"show\": true,\n",
       "            \"scale\": false,\n",
       "            \"nameLocation\": \"end\",\n",
       "            \"nameGap\": 15,\n",
       "            \"gridIndex\": 0,\n",
       "            \"inverse\": false,\n",
       "            \"offset\": 0,\n",
       "            \"splitNumber\": 5,\n",
       "            \"minInterval\": 0,\n",
       "            \"splitLine\": {\n",
       "                \"show\": false,\n",
       "                \"lineStyle\": {\n",
       "                    \"show\": true,\n",
       "                    \"width\": 1,\n",
       "                    \"opacity\": 1,\n",
       "                    \"curveness\": 0,\n",
       "                    \"type\": \"solid\"\n",
       "                }\n",
       "            },\n",
       "            \"data\": [\n",
       "                \"A\",\n",
       "                \"B\",\n",
       "                \"C\",\n",
       "                \"D\",\n",
       "                \"E\",\n",
       "                \"F\",\n",
       "                \"G\"\n",
       "            ]\n",
       "        }\n",
       "    ],\n",
       "    \"yAxis\": [\n",
       "        {\n",
       "            \"show\": true,\n",
       "            \"scale\": false,\n",
       "            \"nameLocation\": \"end\",\n",
       "            \"nameGap\": 15,\n",
       "            \"gridIndex\": 0,\n",
       "            \"inverse\": false,\n",
       "            \"offset\": 0,\n",
       "            \"splitNumber\": 5,\n",
       "            \"minInterval\": 0,\n",
       "            \"splitLine\": {\n",
       "                \"show\": false,\n",
       "                \"lineStyle\": {\n",
       "                    \"show\": true,\n",
       "                    \"width\": 1,\n",
       "                    \"opacity\": 1,\n",
       "                    \"curveness\": 0,\n",
       "                    \"type\": \"solid\"\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    ]\n",
       "};\n",
       "        chart_c53fedcd4b614331884f4144dddd9eff.setOption(option_c53fedcd4b614331884f4144dddd9eff);\n",
       "    </script>\n",
       "</body>\n",
       "</html>\n"
      ],
      "text/plain": [
       "<pyecharts.render.display.HTML at 0x12784cd0>"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bar4=Bar(figsize)\n",
    "bar4.add_xaxis(X)           #分段条图\n",
    "bar4.add_yaxis(\"条1\",Y,stack=\"stack1\")\n",
    "bar4.add_yaxis(\"条2\",Z,stack=\"stack1\")\n",
    "bar4.render_notebook()  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 5.4.2.3 饼图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[['A', 1], ['B', 4], ['C', 7], ['D', 3], ['E', 2], ['F', 5], ['G', 6]]"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "XY = [list(z) for z in zip(X,Y)];XY    #形成饼图数据列表格式 \n",
    "#XY.sort(key=lambda x: x[1]);XY         #数据从小到大排序  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<!DOCTYPE html>\n",
       "<html>\n",
       "<head>\n",
       "    <meta charset=\"UTF-8\">\n",
       "</head>\n",
       "<body>\n",
       "        <div id=\"01c62a6f4fd644a8b9c7f6499042d0da\" class=\"chart-container\" style=\"width:560px; height:380px;\"></div>\n",
       "    <script>\n",
       "        var chart_01c62a6f4fd644a8b9c7f6499042d0da = echarts.init(\n",
       "            document.getElementById('01c62a6f4fd644a8b9c7f6499042d0da'), 'white', {renderer: 'canvas'});\n",
       "        var option_01c62a6f4fd644a8b9c7f6499042d0da = {\n",
       "    \"backgroundColor\": \"white\",\n",
       "    \"animation\": true,\n",
       "    \"animationThreshold\": 2000,\n",
       "    \"animationDuration\": 1000,\n",
       "    \"animationEasing\": \"cubicOut\",\n",
       "    \"animationDelay\": 0,\n",
       "    \"animationDurationUpdate\": 300,\n",
       "    \"animationEasingUpdate\": \"cubicOut\",\n",
       "    \"animationDelayUpdate\": 0,\n",
       "    \"color\": [\n",
       "        \"#c23531\",\n",
       "        \"#2f4554\",\n",
       "        \"#61a0a8\",\n",
       "        \"#d48265\",\n",
       "        \"#749f83\",\n",
       "        \"#ca8622\",\n",
       "        \"#bda29a\",\n",
       "        \"#6e7074\",\n",
       "        \"#546570\",\n",
       "        \"#c4ccd3\",\n",
       "        \"#f05b72\",\n",
       "        \"#ef5b9c\",\n",
       "        \"#f47920\",\n",
       "        \"#905a3d\",\n",
       "        \"#fab27b\",\n",
       "        \"#2a5caa\",\n",
       "        \"#444693\",\n",
       "        \"#726930\",\n",
       "        \"#b2d235\",\n",
       "        \"#6d8346\",\n",
       "        \"#ac6767\",\n",
       "        \"#1d953f\",\n",
       "        \"#6950a1\",\n",
       "        \"#918597\"\n",
       "    ],\n",
       "    \"series\": [\n",
       "        {\n",
       "            \"type\": \"pie\",\n",
       "            \"name\": \"\\u997c\\u56fe\",\n",
       "            \"clockwise\": true,\n",
       "            \"data\": [\n",
       "                {\n",
       "                    \"name\": \"A\",\n",
       "                    \"value\": 1\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"B\",\n",
       "                    \"value\": 4\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"C\",\n",
       "                    \"value\": 7\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"D\",\n",
       "                    \"value\": 3\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"E\",\n",
       "                    \"value\": 2\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"F\",\n",
       "                    \"value\": 5\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"G\",\n",
       "                    \"value\": 6\n",
       "                }\n",
       "            ],\n",
       "            \"radius\": [\n",
       "                \"0%\",\n",
       "                \"75%\"\n",
       "            ],\n",
       "            \"center\": [\n",
       "                \"50%\",\n",
       "                \"50%\"\n",
       "            ],\n",
       "            \"label\": {\n",
       "                \"show\": true,\n",
       "                \"position\": \"top\",\n",
       "                \"margin\": 8\n",
       "            }\n",
       "        }\n",
       "    ],\n",
       "    \"legend\": [\n",
       "        {\n",
       "            \"data\": [\n",
       "                \"A\",\n",
       "                \"B\",\n",
       "                \"C\",\n",
       "                \"D\",\n",
       "                \"E\",\n",
       "                \"F\",\n",
       "                \"G\"\n",
       "            ],\n",
       "            \"selected\": {}\n",
       "        }\n",
       "    ],\n",
       "    \"tooltip\": {\n",
       "        \"show\": true,\n",
       "        \"trigger\": \"item\",\n",
       "        \"triggerOn\": \"mousemove|click\",\n",
       "        \"axisPointer\": {\n",
       "            \"type\": \"line\"\n",
       "        },\n",
       "        \"showContent\": true,\n",
       "        \"alwaysShowContent\": false,\n",
       "        \"showDelay\": 0,\n",
       "        \"hideDelay\": 100,\n",
       "        \"textStyle\": {\n",
       "            \"fontSize\": 14\n",
       "        },\n",
       "        \"borderWidth\": 0,\n",
       "        \"padding\": 5\n",
       "    }\n",
       "};\n",
       "        chart_01c62a6f4fd644a8b9c7f6499042d0da.setOption(option_01c62a6f4fd644a8b9c7f6499042d0da);\n",
       "    </script>\n",
       "</body>\n",
       "</html>\n"
      ],
      "text/plain": [
       "<pyecharts.render.display.HTML at 0x10a08cd0>"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from pyecharts.charts import Pie      #加载pyecharts绘制饼图(Pie)函数\n",
    "Pie(figsize).add(\"饼图\",XY).render_notebook()      "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<!DOCTYPE html>\n",
       "<html>\n",
       "<head>\n",
       "    <meta charset=\"UTF-8\">\n",
       "</head>\n",
       "<body>\n",
       "        <div id=\"36296169f50a486988f8ffa13a655b5c\" class=\"chart-container\" style=\"width:560px; height:380px;\"></div>\n",
       "    <script>\n",
       "        var chart_36296169f50a486988f8ffa13a655b5c = echarts.init(\n",
       "            document.getElementById('36296169f50a486988f8ffa13a655b5c'), 'white', {renderer: 'canvas'});\n",
       "        var option_36296169f50a486988f8ffa13a655b5c = {\n",
       "    \"backgroundColor\": \"white\",\n",
       "    \"animation\": true,\n",
       "    \"animationThreshold\": 2000,\n",
       "    \"animationDuration\": 1000,\n",
       "    \"animationEasing\": \"cubicOut\",\n",
       "    \"animationDelay\": 0,\n",
       "    \"animationDurationUpdate\": 300,\n",
       "    \"animationEasingUpdate\": \"cubicOut\",\n",
       "    \"animationDelayUpdate\": 0,\n",
       "    \"color\": [\n",
       "        \"#c23531\",\n",
       "        \"#2f4554\",\n",
       "        \"#61a0a8\",\n",
       "        \"#d48265\",\n",
       "        \"#749f83\",\n",
       "        \"#ca8622\",\n",
       "        \"#bda29a\",\n",
       "        \"#6e7074\",\n",
       "        \"#546570\",\n",
       "        \"#c4ccd3\",\n",
       "        \"#f05b72\",\n",
       "        \"#ef5b9c\",\n",
       "        \"#f47920\",\n",
       "        \"#905a3d\",\n",
       "        \"#fab27b\",\n",
       "        \"#2a5caa\",\n",
       "        \"#444693\",\n",
       "        \"#726930\",\n",
       "        \"#b2d235\",\n",
       "        \"#6d8346\",\n",
       "        \"#ac6767\",\n",
       "        \"#1d953f\",\n",
       "        \"#6950a1\",\n",
       "        \"#918597\"\n",
       "    ],\n",
       "    \"series\": [\n",
       "        {\n",
       "            \"type\": \"pie\",\n",
       "            \"clockwise\": true,\n",
       "            \"data\": [\n",
       "                {\n",
       "                    \"name\": \"A\",\n",
       "                    \"value\": 1\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"B\",\n",
       "                    \"value\": 4\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"C\",\n",
       "                    \"value\": 7\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"D\",\n",
       "                    \"value\": 3\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"E\",\n",
       "                    \"value\": 2\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"F\",\n",
       "                    \"value\": 5\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"G\",\n",
       "                    \"value\": 6\n",
       "                }\n",
       "            ],\n",
       "            \"radius\": [\n",
       "                \"0%\",\n",
       "                \"75%\"\n",
       "            ],\n",
       "            \"center\": [\n",
       "                \"50%\",\n",
       "                \"50%\"\n",
       "            ],\n",
       "            \"label\": {\n",
       "                \"show\": true,\n",
       "                \"position\": \"top\",\n",
       "                \"margin\": 8,\n",
       "                \"formatter\": \"{b}:{c}\"\n",
       "            },\n",
       "            \"rippleEffect\": {\n",
       "                \"show\": true,\n",
       "                \"brushType\": \"stroke\",\n",
       "                \"scale\": 2.5,\n",
       "                \"period\": 4\n",
       "            }\n",
       "        }\n",
       "    ],\n",
       "    \"legend\": [\n",
       "        {\n",
       "            \"data\": [\n",
       "                \"A\",\n",
       "                \"B\",\n",
       "                \"C\",\n",
       "                \"D\",\n",
       "                \"E\",\n",
       "                \"F\",\n",
       "                \"G\"\n",
       "            ],\n",
       "            \"selected\": {}\n",
       "        }\n",
       "    ],\n",
       "    \"tooltip\": {\n",
       "        \"show\": true,\n",
       "        \"trigger\": \"item\",\n",
       "        \"triggerOn\": \"mousemove|click\",\n",
       "        \"axisPointer\": {\n",
       "            \"type\": \"line\"\n",
       "        },\n",
       "        \"showContent\": true,\n",
       "        \"alwaysShowContent\": false,\n",
       "        \"showDelay\": 0,\n",
       "        \"hideDelay\": 100,\n",
       "        \"textStyle\": {\n",
       "            \"fontSize\": 14\n",
       "        },\n",
       "        \"borderWidth\": 0,\n",
       "        \"padding\": 5\n",
       "    }\n",
       "};\n",
       "        chart_36296169f50a486988f8ffa13a655b5c.setOption(option_36296169f50a486988f8ffa13a655b5c);\n",
       "    </script>\n",
       "</body>\n",
       "</html>\n"
      ],
      "text/plain": [
       "<pyecharts.render.display.HTML at 0x10ae6400>"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(Pie(figsize)\n",
    "     .add(\"\",XY)\n",
    "     .set_series_opts(opts.LabelOpts(formatter=\"{b}:{c}\")) #加标签饼图 \n",
    "     .render_notebook() \n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<!DOCTYPE html>\n",
       "<html>\n",
       "<head>\n",
       "    <meta charset=\"UTF-8\">\n",
       "</head>\n",
       "<body>\n",
       "        <div id=\"f0d0f75399c54d9a996a2b323d5b2f88\" class=\"chart-container\" style=\"width:560px; height:380px;\"></div>\n",
       "    <script>\n",
       "        var chart_f0d0f75399c54d9a996a2b323d5b2f88 = echarts.init(\n",
       "            document.getElementById('f0d0f75399c54d9a996a2b323d5b2f88'), 'white', {renderer: 'canvas'});\n",
       "        var option_f0d0f75399c54d9a996a2b323d5b2f88 = {\n",
       "    \"backgroundColor\": \"white\",\n",
       "    \"animation\": true,\n",
       "    \"animationThreshold\": 2000,\n",
       "    \"animationDuration\": 1000,\n",
       "    \"animationEasing\": \"cubicOut\",\n",
       "    \"animationDelay\": 0,\n",
       "    \"animationDurationUpdate\": 300,\n",
       "    \"animationEasingUpdate\": \"cubicOut\",\n",
       "    \"animationDelayUpdate\": 0,\n",
       "    \"color\": [\n",
       "        \"#c23531\",\n",
       "        \"#2f4554\",\n",
       "        \"#61a0a8\",\n",
       "        \"#d48265\",\n",
       "        \"#749f83\",\n",
       "        \"#ca8622\",\n",
       "        \"#bda29a\",\n",
       "        \"#6e7074\",\n",
       "        \"#546570\",\n",
       "        \"#c4ccd3\",\n",
       "        \"#f05b72\",\n",
       "        \"#ef5b9c\",\n",
       "        \"#f47920\",\n",
       "        \"#905a3d\",\n",
       "        \"#fab27b\",\n",
       "        \"#2a5caa\",\n",
       "        \"#444693\",\n",
       "        \"#726930\",\n",
       "        \"#b2d235\",\n",
       "        \"#6d8346\",\n",
       "        \"#ac6767\",\n",
       "        \"#1d953f\",\n",
       "        \"#6950a1\",\n",
       "        \"#918597\"\n",
       "    ],\n",
       "    \"series\": [\n",
       "        {\n",
       "            \"type\": \"pie\",\n",
       "            \"name\": \"\\u73ab\\u7470\\u997c\\u56fe\",\n",
       "            \"clockwise\": true,\n",
       "            \"data\": [\n",
       "                {\n",
       "                    \"name\": \"A\",\n",
       "                    \"value\": 1\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"B\",\n",
       "                    \"value\": 4\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"C\",\n",
       "                    \"value\": 7\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"D\",\n",
       "                    \"value\": 3\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"E\",\n",
       "                    \"value\": 2\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"F\",\n",
       "                    \"value\": 5\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"G\",\n",
       "                    \"value\": 6\n",
       "                }\n",
       "            ],\n",
       "            \"radius\": [\n",
       "                \"0%\",\n",
       "                \"75%\"\n",
       "            ],\n",
       "            \"center\": [\n",
       "                \"50%\",\n",
       "                \"50%\"\n",
       "            ],\n",
       "            \"roseType\": \"radius\",\n",
       "            \"label\": {\n",
       "                \"show\": true,\n",
       "                \"position\": \"top\",\n",
       "                \"margin\": 8\n",
       "            }\n",
       "        }\n",
       "    ],\n",
       "    \"legend\": [\n",
       "        {\n",
       "            \"data\": [\n",
       "                \"A\",\n",
       "                \"B\",\n",
       "                \"C\",\n",
       "                \"D\",\n",
       "                \"E\",\n",
       "                \"F\",\n",
       "                \"G\"\n",
       "            ],\n",
       "            \"selected\": {}\n",
       "        }\n",
       "    ],\n",
       "    \"tooltip\": {\n",
       "        \"show\": true,\n",
       "        \"trigger\": \"item\",\n",
       "        \"triggerOn\": \"mousemove|click\",\n",
       "        \"axisPointer\": {\n",
       "            \"type\": \"line\"\n",
       "        },\n",
       "        \"showContent\": true,\n",
       "        \"alwaysShowContent\": false,\n",
       "        \"showDelay\": 0,\n",
       "        \"hideDelay\": 100,\n",
       "        \"textStyle\": {\n",
       "            \"fontSize\": 14\n",
       "        },\n",
       "        \"borderWidth\": 0,\n",
       "        \"padding\": 5\n",
       "    }\n",
       "};\n",
       "        chart_f0d0f75399c54d9a996a2b323d5b2f88.setOption(option_f0d0f75399c54d9a996a2b323d5b2f88);\n",
       "    </script>\n",
       "</body>\n",
       "</html>\n"
      ],
      "text/plain": [
       "<pyecharts.render.display.HTML at 0x12726160>"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Pie(figsize).add(\"玫瑰饼图\",XY,rosetype=\"radius\").render_notebook()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<!DOCTYPE html>\n",
       "<html>\n",
       "<head>\n",
       "    <meta charset=\"UTF-8\">\n",
       "</head>\n",
       "<body>\n",
       "        <div id=\"435eecb81cb24f5baf9c6ebb366ef981\" class=\"chart-container\" style=\"width:560px; height:380px;\"></div>\n",
       "    <script>\n",
       "        var chart_435eecb81cb24f5baf9c6ebb366ef981 = echarts.init(\n",
       "            document.getElementById('435eecb81cb24f5baf9c6ebb366ef981'), 'white', {renderer: 'canvas'});\n",
       "        var option_435eecb81cb24f5baf9c6ebb366ef981 = {\n",
       "    \"backgroundColor\": \"white\",\n",
       "    \"animation\": true,\n",
       "    \"animationThreshold\": 2000,\n",
       "    \"animationDuration\": 1000,\n",
       "    \"animationEasing\": \"cubicOut\",\n",
       "    \"animationDelay\": 0,\n",
       "    \"animationDurationUpdate\": 300,\n",
       "    \"animationEasingUpdate\": \"cubicOut\",\n",
       "    \"animationDelayUpdate\": 0,\n",
       "    \"color\": [\n",
       "        \"#c23531\",\n",
       "        \"#2f4554\",\n",
       "        \"#61a0a8\",\n",
       "        \"#d48265\",\n",
       "        \"#749f83\",\n",
       "        \"#ca8622\",\n",
       "        \"#bda29a\",\n",
       "        \"#6e7074\",\n",
       "        \"#546570\",\n",
       "        \"#c4ccd3\",\n",
       "        \"#f05b72\",\n",
       "        \"#ef5b9c\",\n",
       "        \"#f47920\",\n",
       "        \"#905a3d\",\n",
       "        \"#fab27b\",\n",
       "        \"#2a5caa\",\n",
       "        \"#444693\",\n",
       "        \"#726930\",\n",
       "        \"#b2d235\",\n",
       "        \"#6d8346\",\n",
       "        \"#ac6767\",\n",
       "        \"#1d953f\",\n",
       "        \"#6950a1\",\n",
       "        \"#918597\"\n",
       "    ],\n",
       "    \"series\": [\n",
       "        {\n",
       "            \"type\": \"pie\",\n",
       "            \"name\": \"\\u5706\\u5708\\u56fe\",\n",
       "            \"clockwise\": true,\n",
       "            \"data\": [\n",
       "                {\n",
       "                    \"name\": \"A\",\n",
       "                    \"value\": 1\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"B\",\n",
       "                    \"value\": 4\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"C\",\n",
       "                    \"value\": 7\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"D\",\n",
       "                    \"value\": 3\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"E\",\n",
       "                    \"value\": 2\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"F\",\n",
       "                    \"value\": 5\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"G\",\n",
       "                    \"value\": 6\n",
       "                }\n",
       "            ],\n",
       "            \"radius\": [\n",
       "                \"10%\",\n",
       "                \"75%\"\n",
       "            ],\n",
       "            \"center\": [\n",
       "                \"50%\",\n",
       "                \"50%\"\n",
       "            ],\n",
       "            \"label\": {\n",
       "                \"show\": true,\n",
       "                \"position\": \"top\",\n",
       "                \"margin\": 8\n",
       "            }\n",
       "        }\n",
       "    ],\n",
       "    \"legend\": [\n",
       "        {\n",
       "            \"data\": [\n",
       "                \"A\",\n",
       "                \"B\",\n",
       "                \"C\",\n",
       "                \"D\",\n",
       "                \"E\",\n",
       "                \"F\",\n",
       "                \"G\"\n",
       "            ],\n",
       "            \"selected\": {}\n",
       "        }\n",
       "    ],\n",
       "    \"tooltip\": {\n",
       "        \"show\": true,\n",
       "        \"trigger\": \"item\",\n",
       "        \"triggerOn\": \"mousemove|click\",\n",
       "        \"axisPointer\": {\n",
       "            \"type\": \"line\"\n",
       "        },\n",
       "        \"showContent\": true,\n",
       "        \"alwaysShowContent\": false,\n",
       "        \"showDelay\": 0,\n",
       "        \"hideDelay\": 100,\n",
       "        \"textStyle\": {\n",
       "            \"fontSize\": 14\n",
       "        },\n",
       "        \"borderWidth\": 0,\n",
       "        \"padding\": 5\n",
       "    }\n",
       "};\n",
       "        chart_435eecb81cb24f5baf9c6ebb366ef981.setOption(option_435eecb81cb24f5baf9c6ebb366ef981);\n",
       "    </script>\n",
       "</body>\n",
       "</html>\n"
      ],
      "text/plain": [
       "<pyecharts.render.display.HTML at 0x12765790>"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Pie(figsize).add('圆圈图',XY,radius=['10%','75%']).render_notebook()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 5.4.2.4 漏斗图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<!DOCTYPE html>\n",
       "<html>\n",
       "<head>\n",
       "    <meta charset=\"UTF-8\">\n",
       "</head>\n",
       "<body>\n",
       "        <div id=\"f87c7d278ae74c619f79100178ebe009\" class=\"chart-container\" style=\"width:560px; height:380px;\"></div>\n",
       "    <script>\n",
       "        var chart_f87c7d278ae74c619f79100178ebe009 = echarts.init(\n",
       "            document.getElementById('f87c7d278ae74c619f79100178ebe009'), 'white', {renderer: 'canvas'});\n",
       "        var option_f87c7d278ae74c619f79100178ebe009 = {\n",
       "    \"backgroundColor\": \"white\",\n",
       "    \"animation\": true,\n",
       "    \"animationThreshold\": 2000,\n",
       "    \"animationDuration\": 1000,\n",
       "    \"animationEasing\": \"cubicOut\",\n",
       "    \"animationDelay\": 0,\n",
       "    \"animationDurationUpdate\": 300,\n",
       "    \"animationEasingUpdate\": \"cubicOut\",\n",
       "    \"animationDelayUpdate\": 0,\n",
       "    \"color\": [\n",
       "        \"#c23531\",\n",
       "        \"#2f4554\",\n",
       "        \"#61a0a8\",\n",
       "        \"#d48265\",\n",
       "        \"#749f83\",\n",
       "        \"#ca8622\",\n",
       "        \"#bda29a\",\n",
       "        \"#6e7074\",\n",
       "        \"#546570\",\n",
       "        \"#c4ccd3\",\n",
       "        \"#f05b72\",\n",
       "        \"#ef5b9c\",\n",
       "        \"#f47920\",\n",
       "        \"#905a3d\",\n",
       "        \"#fab27b\",\n",
       "        \"#2a5caa\",\n",
       "        \"#444693\",\n",
       "        \"#726930\",\n",
       "        \"#b2d235\",\n",
       "        \"#6d8346\",\n",
       "        \"#ac6767\",\n",
       "        \"#1d953f\",\n",
       "        \"#6950a1\",\n",
       "        \"#918597\"\n",
       "    ],\n",
       "    \"series\": [\n",
       "        {\n",
       "            \"type\": \"funnel\",\n",
       "            \"name\": \"\\u6f0f\\u6597\\u56fe\",\n",
       "            \"data\": [\n",
       "                {\n",
       "                    \"name\": \"A\",\n",
       "                    \"value\": 1\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"B\",\n",
       "                    \"value\": 4\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"C\",\n",
       "                    \"value\": 7\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"D\",\n",
       "                    \"value\": 3\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"E\",\n",
       "                    \"value\": 2\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"F\",\n",
       "                    \"value\": 5\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"G\",\n",
       "                    \"value\": 6\n",
       "                }\n",
       "            ],\n",
       "            \"sort\": \"descending\",\n",
       "            \"gap\": 0,\n",
       "            \"label\": {\n",
       "                \"show\": true,\n",
       "                \"position\": \"top\",\n",
       "                \"margin\": 8\n",
       "            }\n",
       "        }\n",
       "    ],\n",
       "    \"legend\": [\n",
       "        {\n",
       "            \"data\": [\n",
       "                \"C\",\n",
       "                \"B\",\n",
       "                \"F\",\n",
       "                \"D\",\n",
       "                \"A\",\n",
       "                \"G\",\n",
       "                \"E\"\n",
       "            ],\n",
       "            \"selected\": {\n",
       "                \"A\": true,\n",
       "                \"B\": true,\n",
       "                \"C\": true,\n",
       "                \"D\": true,\n",
       "                \"E\": true,\n",
       "                \"F\": true,\n",
       "                \"G\": true\n",
       "            }\n",
       "        }\n",
       "    ],\n",
       "    \"tooltip\": {\n",
       "        \"show\": true,\n",
       "        \"trigger\": \"item\",\n",
       "        \"triggerOn\": \"mousemove|click\",\n",
       "        \"axisPointer\": {\n",
       "            \"type\": \"line\"\n",
       "        },\n",
       "        \"showContent\": true,\n",
       "        \"alwaysShowContent\": false,\n",
       "        \"showDelay\": 0,\n",
       "        \"hideDelay\": 100,\n",
       "        \"textStyle\": {\n",
       "            \"fontSize\": 14\n",
       "        },\n",
       "        \"borderWidth\": 0,\n",
       "        \"padding\": 5\n",
       "    }\n",
       "};\n",
       "        chart_f87c7d278ae74c619f79100178ebe009.setOption(option_f87c7d278ae74c619f79100178ebe009);\n",
       "    </script>\n",
       "</body>\n",
       "</html>\n"
      ],
      "text/plain": [
       "<pyecharts.render.display.HTML at 0x12726880>"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from pyecharts.charts import Funnel\n",
    "fun1=Funnel(figsize)\n",
    "fun1.add(\"漏斗图\", XY)\n",
    "fun1.render_notebook()\n",
    "#Funnel(figsize).add(\"漏斗图\", XY).render_notebook()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<!DOCTYPE html>\n",
       "<html>\n",
       "<head>\n",
       "    <meta charset=\"UTF-8\">\n",
       "</head>\n",
       "<body>\n",
       "        <div id=\"a8845244b55a48bea0574ec31d5f2339\" class=\"chart-container\" style=\"width:560px; height:380px;\"></div>\n",
       "    <script>\n",
       "        var chart_a8845244b55a48bea0574ec31d5f2339 = echarts.init(\n",
       "            document.getElementById('a8845244b55a48bea0574ec31d5f2339'), 'white', {renderer: 'canvas'});\n",
       "        var option_a8845244b55a48bea0574ec31d5f2339 = {\n",
       "    \"backgroundColor\": \"white\",\n",
       "    \"animation\": true,\n",
       "    \"animationThreshold\": 2000,\n",
       "    \"animationDuration\": 1000,\n",
       "    \"animationEasing\": \"cubicOut\",\n",
       "    \"animationDelay\": 0,\n",
       "    \"animationDurationUpdate\": 300,\n",
       "    \"animationEasingUpdate\": \"cubicOut\",\n",
       "    \"animationDelayUpdate\": 0,\n",
       "    \"color\": [\n",
       "        \"#c23531\",\n",
       "        \"#2f4554\",\n",
       "        \"#61a0a8\",\n",
       "        \"#d48265\",\n",
       "        \"#749f83\",\n",
       "        \"#ca8622\",\n",
       "        \"#bda29a\",\n",
       "        \"#6e7074\",\n",
       "        \"#546570\",\n",
       "        \"#c4ccd3\",\n",
       "        \"#f05b72\",\n",
       "        \"#ef5b9c\",\n",
       "        \"#f47920\",\n",
       "        \"#905a3d\",\n",
       "        \"#fab27b\",\n",
       "        \"#2a5caa\",\n",
       "        \"#444693\",\n",
       "        \"#726930\",\n",
       "        \"#b2d235\",\n",
       "        \"#6d8346\",\n",
       "        \"#ac6767\",\n",
       "        \"#1d953f\",\n",
       "        \"#6950a1\",\n",
       "        \"#918597\"\n",
       "    ],\n",
       "    \"series\": [\n",
       "        {\n",
       "            \"type\": \"funnel\",\n",
       "            \"name\": \"\\u6f0f\\u6597\\u56fe\",\n",
       "            \"data\": [\n",
       "                {\n",
       "                    \"name\": \"A\",\n",
       "                    \"value\": 1\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"B\",\n",
       "                    \"value\": 4\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"C\",\n",
       "                    \"value\": 7\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"D\",\n",
       "                    \"value\": 3\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"E\",\n",
       "                    \"value\": 2\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"F\",\n",
       "                    \"value\": 5\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"G\",\n",
       "                    \"value\": 6\n",
       "                }\n",
       "            ],\n",
       "            \"sort\": \"descending\",\n",
       "            \"gap\": 0,\n",
       "            \"label\": {\n",
       "                \"show\": true,\n",
       "                \"position\": \"inside\",\n",
       "                \"margin\": 8\n",
       "            }\n",
       "        }\n",
       "    ],\n",
       "    \"legend\": [\n",
       "        {\n",
       "            \"data\": [\n",
       "                \"C\",\n",
       "                \"B\",\n",
       "                \"F\",\n",
       "                \"D\",\n",
       "                \"A\",\n",
       "                \"G\",\n",
       "                \"E\"\n",
       "            ],\n",
       "            \"selected\": {\n",
       "                \"A\": true,\n",
       "                \"B\": true,\n",
       "                \"C\": true,\n",
       "                \"D\": true,\n",
       "                \"E\": true,\n",
       "                \"F\": true,\n",
       "                \"G\": true\n",
       "            }\n",
       "        }\n",
       "    ],\n",
       "    \"tooltip\": {\n",
       "        \"show\": true,\n",
       "        \"trigger\": \"item\",\n",
       "        \"triggerOn\": \"mousemove|click\",\n",
       "        \"axisPointer\": {\n",
       "            \"type\": \"line\"\n",
       "        },\n",
       "        \"showContent\": true,\n",
       "        \"alwaysShowContent\": false,\n",
       "        \"showDelay\": 0,\n",
       "        \"hideDelay\": 100,\n",
       "        \"textStyle\": {\n",
       "            \"fontSize\": 14\n",
       "        },\n",
       "        \"borderWidth\": 0,\n",
       "        \"padding\": 5\n",
       "    }\n",
       "};\n",
       "        chart_a8845244b55a48bea0574ec31d5f2339.setOption(option_a8845244b55a48bea0574ec31d5f2339);\n",
       "    </script>\n",
       "</body>\n",
       "</html>\n"
      ],
      "text/plain": [
       "<pyecharts.render.display.HTML at 0x127c4130>"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fun2=Funnel(figsize)\n",
    "fun2.add(\"漏斗图\", XY,label_opts=opts.LabelOpts(position=\"inside\"))     \n",
    "fun2.render_notebook()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 5.4.2.5 折线图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<!DOCTYPE html>\n",
       "<html>\n",
       "<head>\n",
       "    <meta charset=\"UTF-8\">\n",
       "</head>\n",
       "<body>\n",
       "        <div id=\"fbaafe1592d941599f54a8814e1ca1f8\" class=\"chart-container\" style=\"width:560px; height:380px;\"></div>\n",
       "    <script>\n",
       "        var chart_fbaafe1592d941599f54a8814e1ca1f8 = echarts.init(\n",
       "            document.getElementById('fbaafe1592d941599f54a8814e1ca1f8'), 'white', {renderer: 'canvas'});\n",
       "        var option_fbaafe1592d941599f54a8814e1ca1f8 = {\n",
       "    \"backgroundColor\": \"white\",\n",
       "    \"animation\": true,\n",
       "    \"animationThreshold\": 2000,\n",
       "    \"animationDuration\": 1000,\n",
       "    \"animationEasing\": \"cubicOut\",\n",
       "    \"animationDelay\": 0,\n",
       "    \"animationDurationUpdate\": 300,\n",
       "    \"animationEasingUpdate\": \"cubicOut\",\n",
       "    \"animationDelayUpdate\": 0,\n",
       "    \"color\": [\n",
       "        \"#c23531\",\n",
       "        \"#2f4554\",\n",
       "        \"#61a0a8\",\n",
       "        \"#d48265\",\n",
       "        \"#749f83\",\n",
       "        \"#ca8622\",\n",
       "        \"#bda29a\",\n",
       "        \"#6e7074\",\n",
       "        \"#546570\",\n",
       "        \"#c4ccd3\",\n",
       "        \"#f05b72\",\n",
       "        \"#ef5b9c\",\n",
       "        \"#f47920\",\n",
       "        \"#905a3d\",\n",
       "        \"#fab27b\",\n",
       "        \"#2a5caa\",\n",
       "        \"#444693\",\n",
       "        \"#726930\",\n",
       "        \"#b2d235\",\n",
       "        \"#6d8346\",\n",
       "        \"#ac6767\",\n",
       "        \"#1d953f\",\n",
       "        \"#6950a1\",\n",
       "        \"#918597\"\n",
       "    ],\n",
       "    \"series\": [\n",
       "        {\n",
       "            \"type\": \"line\",\n",
       "            \"name\": \"\\u7ebf\\u56fe\",\n",
       "            \"connectNulls\": false,\n",
       "            \"symbolSize\": 4,\n",
       "            \"showSymbol\": true,\n",
       "            \"smooth\": false,\n",
       "            \"clip\": true,\n",
       "            \"step\": false,\n",
       "            \"data\": [\n",
       "                [\n",
       "                    \"A\",\n",
       "                    1\n",
       "                ],\n",
       "                [\n",
       "                    \"B\",\n",
       "                    4\n",
       "                ],\n",
       "                [\n",
       "                    \"C\",\n",
       "                    7\n",
       "                ],\n",
       "                [\n",
       "                    \"D\",\n",
       "                    3\n",
       "                ],\n",
       "                [\n",
       "                    \"E\",\n",
       "                    2\n",
       "                ],\n",
       "                [\n",
       "                    \"F\",\n",
       "                    5\n",
       "                ],\n",
       "                [\n",
       "                    \"G\",\n",
       "                    6\n",
       "                ]\n",
       "            ],\n",
       "            \"hoverAnimation\": true,\n",
       "            \"label\": {\n",
       "                \"show\": true,\n",
       "                \"position\": \"top\",\n",
       "                \"margin\": 8\n",
       "            },\n",
       "            \"lineStyle\": {\n",
       "                \"show\": true,\n",
       "                \"width\": 1,\n",
       "                \"opacity\": 1,\n",
       "                \"curveness\": 0,\n",
       "                \"type\": \"solid\"\n",
       "            },\n",
       "            \"areaStyle\": {\n",
       "                \"opacity\": 0\n",
       "            },\n",
       "            \"zlevel\": 0,\n",
       "            \"z\": 0\n",
       "        }\n",
       "    ],\n",
       "    \"legend\": [\n",
       "        {\n",
       "            \"data\": [\n",
       "                \"\\u7ebf\\u56fe\"\n",
       "            ],\n",
       "            \"selected\": {\n",
       "                \"\\u7ebf\\u56fe\": true\n",
       "            }\n",
       "        }\n",
       "    ],\n",
       "    \"tooltip\": {\n",
       "        \"show\": true,\n",
       "        \"trigger\": \"item\",\n",
       "        \"triggerOn\": \"mousemove|click\",\n",
       "        \"axisPointer\": {\n",
       "            \"type\": \"line\"\n",
       "        },\n",
       "        \"showContent\": true,\n",
       "        \"alwaysShowContent\": false,\n",
       "        \"showDelay\": 0,\n",
       "        \"hideDelay\": 100,\n",
       "        \"textStyle\": {\n",
       "            \"fontSize\": 14\n",
       "        },\n",
       "        \"borderWidth\": 0,\n",
       "        \"padding\": 5\n",
       "    },\n",
       "    \"xAxis\": [\n",
       "        {\n",
       "            \"show\": true,\n",
       "            \"scale\": false,\n",
       "            \"nameLocation\": \"end\",\n",
       "            \"nameGap\": 15,\n",
       "            \"gridIndex\": 0,\n",
       "            \"inverse\": false,\n",
       "            \"offset\": 0,\n",
       "            \"splitNumber\": 5,\n",
       "            \"minInterval\": 0,\n",
       "            \"splitLine\": {\n",
       "                \"show\": false,\n",
       "                \"lineStyle\": {\n",
       "                    \"show\": true,\n",
       "                    \"width\": 1,\n",
       "                    \"opacity\": 1,\n",
       "                    \"curveness\": 0,\n",
       "                    \"type\": \"solid\"\n",
       "                }\n",
       "            },\n",
       "            \"data\": [\n",
       "                \"A\",\n",
       "                \"B\",\n",
       "                \"C\",\n",
       "                \"D\",\n",
       "                \"E\",\n",
       "                \"F\",\n",
       "                \"G\"\n",
       "            ]\n",
       "        }\n",
       "    ],\n",
       "    \"yAxis\": [\n",
       "        {\n",
       "            \"show\": true,\n",
       "            \"scale\": false,\n",
       "            \"nameLocation\": \"end\",\n",
       "            \"nameGap\": 15,\n",
       "            \"gridIndex\": 0,\n",
       "            \"inverse\": false,\n",
       "            \"offset\": 0,\n",
       "            \"splitNumber\": 5,\n",
       "            \"minInterval\": 0,\n",
       "            \"splitLine\": {\n",
       "                \"show\": false,\n",
       "                \"lineStyle\": {\n",
       "                    \"show\": true,\n",
       "                    \"width\": 1,\n",
       "                    \"opacity\": 1,\n",
       "                    \"curveness\": 0,\n",
       "                    \"type\": \"solid\"\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    ]\n",
       "};\n",
       "        chart_fbaafe1592d941599f54a8814e1ca1f8.setOption(option_fbaafe1592d941599f54a8814e1ca1f8);\n",
       "    </script>\n",
       "</body>\n",
       "</html>\n"
      ],
      "text/plain": [
       "<pyecharts.render.display.HTML at 0x12726760>"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from pyecharts.charts import Line  #加载pyecharts绘制线图（Line）函数\n",
    "Line(figsize).add_xaxis(X).add_yaxis('线图',Y).render_notebook()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<!DOCTYPE html>\n",
       "<html>\n",
       "<head>\n",
       "    <meta charset=\"UTF-8\">\n",
       "</head>\n",
       "<body>\n",
       "        <div id=\"8c6f387ca5e14c4f9965a71fe6576318\" class=\"chart-container\" style=\"width:560px; height:380px;\"></div>\n",
       "    <script>\n",
       "        var chart_8c6f387ca5e14c4f9965a71fe6576318 = echarts.init(\n",
       "            document.getElementById('8c6f387ca5e14c4f9965a71fe6576318'), 'white', {renderer: 'canvas'});\n",
       "        var option_8c6f387ca5e14c4f9965a71fe6576318 = {\n",
       "    \"backgroundColor\": \"white\",\n",
       "    \"animation\": true,\n",
       "    \"animationThreshold\": 2000,\n",
       "    \"animationDuration\": 1000,\n",
       "    \"animationEasing\": \"cubicOut\",\n",
       "    \"animationDelay\": 0,\n",
       "    \"animationDurationUpdate\": 300,\n",
       "    \"animationEasingUpdate\": \"cubicOut\",\n",
       "    \"animationDelayUpdate\": 0,\n",
       "    \"color\": [\n",
       "        \"#c23531\",\n",
       "        \"#2f4554\",\n",
       "        \"#61a0a8\",\n",
       "        \"#d48265\",\n",
       "        \"#749f83\",\n",
       "        \"#ca8622\",\n",
       "        \"#bda29a\",\n",
       "        \"#6e7074\",\n",
       "        \"#546570\",\n",
       "        \"#c4ccd3\",\n",
       "        \"#f05b72\",\n",
       "        \"#ef5b9c\",\n",
       "        \"#f47920\",\n",
       "        \"#905a3d\",\n",
       "        \"#fab27b\",\n",
       "        \"#2a5caa\",\n",
       "        \"#444693\",\n",
       "        \"#726930\",\n",
       "        \"#b2d235\",\n",
       "        \"#6d8346\",\n",
       "        \"#ac6767\",\n",
       "        \"#1d953f\",\n",
       "        \"#6950a1\",\n",
       "        \"#918597\"\n",
       "    ],\n",
       "    \"series\": [\n",
       "        {\n",
       "            \"type\": \"line\",\n",
       "            \"name\": \"\\u7ebf1\",\n",
       "            \"connectNulls\": false,\n",
       "            \"symbolSize\": 4,\n",
       "            \"showSymbol\": true,\n",
       "            \"smooth\": false,\n",
       "            \"clip\": true,\n",
       "            \"step\": false,\n",
       "            \"data\": [\n",
       "                [\n",
       "                    \"A\",\n",
       "                    1\n",
       "                ],\n",
       "                [\n",
       "                    \"B\",\n",
       "                    4\n",
       "                ],\n",
       "                [\n",
       "                    \"C\",\n",
       "                    7\n",
       "                ],\n",
       "                [\n",
       "                    \"D\",\n",
       "                    3\n",
       "                ],\n",
       "                [\n",
       "                    \"E\",\n",
       "                    2\n",
       "                ],\n",
       "                [\n",
       "                    \"F\",\n",
       "                    5\n",
       "                ],\n",
       "                [\n",
       "                    \"G\",\n",
       "                    6\n",
       "                ]\n",
       "            ],\n",
       "            \"hoverAnimation\": true,\n",
       "            \"label\": {\n",
       "                \"show\": true,\n",
       "                \"position\": \"top\",\n",
       "                \"margin\": 8\n",
       "            },\n",
       "            \"lineStyle\": {\n",
       "                \"show\": true,\n",
       "                \"width\": 1,\n",
       "                \"opacity\": 1,\n",
       "                \"curveness\": 0,\n",
       "                \"type\": \"solid\"\n",
       "            },\n",
       "            \"areaStyle\": {\n",
       "                \"opacity\": 0\n",
       "            },\n",
       "            \"zlevel\": 0,\n",
       "            \"z\": 0\n",
       "        },\n",
       "        {\n",
       "            \"type\": \"line\",\n",
       "            \"name\": \"\\u7ebf2\",\n",
       "            \"connectNulls\": false,\n",
       "            \"symbolSize\": 4,\n",
       "            \"showSymbol\": true,\n",
       "            \"smooth\": false,\n",
       "            \"clip\": true,\n",
       "            \"step\": false,\n",
       "            \"data\": [\n",
       "                [\n",
       "                    \"A\",\n",
       "                    6\n",
       "                ],\n",
       "                [\n",
       "                    \"B\",\n",
       "                    5\n",
       "                ],\n",
       "                [\n",
       "                    \"C\",\n",
       "                    3\n",
       "                ],\n",
       "                [\n",
       "                    \"D\",\n",
       "                    2\n",
       "                ],\n",
       "                [\n",
       "                    \"E\",\n",
       "                    7\n",
       "                ],\n",
       "                [\n",
       "                    \"F\",\n",
       "                    4\n",
       "                ],\n",
       "                [\n",
       "                    \"G\",\n",
       "                    1\n",
       "                ]\n",
       "            ],\n",
       "            \"hoverAnimation\": true,\n",
       "            \"label\": {\n",
       "                \"show\": true,\n",
       "                \"position\": \"top\",\n",
       "                \"margin\": 8\n",
       "            },\n",
       "            \"lineStyle\": {\n",
       "                \"show\": true,\n",
       "                \"width\": 1,\n",
       "                \"opacity\": 1,\n",
       "                \"curveness\": 0,\n",
       "                \"type\": \"solid\"\n",
       "            },\n",
       "            \"areaStyle\": {\n",
       "                \"opacity\": 0\n",
       "            },\n",
       "            \"zlevel\": 0,\n",
       "            \"z\": 0\n",
       "        }\n",
       "    ],\n",
       "    \"legend\": [\n",
       "        {\n",
       "            \"data\": [\n",
       "                \"\\u7ebf1\",\n",
       "                \"\\u7ebf2\"\n",
       "            ],\n",
       "            \"selected\": {\n",
       "                \"\\u7ebf1\": true,\n",
       "                \"\\u7ebf2\": true\n",
       "            }\n",
       "        }\n",
       "    ],\n",
       "    \"tooltip\": {\n",
       "        \"show\": true,\n",
       "        \"trigger\": \"item\",\n",
       "        \"triggerOn\": \"mousemove|click\",\n",
       "        \"axisPointer\": {\n",
       "            \"type\": \"line\"\n",
       "        },\n",
       "        \"showContent\": true,\n",
       "        \"alwaysShowContent\": false,\n",
       "        \"showDelay\": 0,\n",
       "        \"hideDelay\": 100,\n",
       "        \"textStyle\": {\n",
       "            \"fontSize\": 14\n",
       "        },\n",
       "        \"borderWidth\": 0,\n",
       "        \"padding\": 5\n",
       "    },\n",
       "    \"xAxis\": [\n",
       "        {\n",
       "            \"show\": true,\n",
       "            \"scale\": false,\n",
       "            \"nameLocation\": \"end\",\n",
       "            \"nameGap\": 15,\n",
       "            \"gridIndex\": 0,\n",
       "            \"inverse\": false,\n",
       "            \"offset\": 0,\n",
       "            \"splitNumber\": 5,\n",
       "            \"minInterval\": 0,\n",
       "            \"splitLine\": {\n",
       "                \"show\": false,\n",
       "                \"lineStyle\": {\n",
       "                    \"show\": true,\n",
       "                    \"width\": 1,\n",
       "                    \"opacity\": 1,\n",
       "                    \"curveness\": 0,\n",
       "                    \"type\": \"solid\"\n",
       "                }\n",
       "            },\n",
       "            \"data\": [\n",
       "                \"A\",\n",
       "                \"B\",\n",
       "                \"C\",\n",
       "                \"D\",\n",
       "                \"E\",\n",
       "                \"F\",\n",
       "                \"G\"\n",
       "            ]\n",
       "        }\n",
       "    ],\n",
       "    \"yAxis\": [\n",
       "        {\n",
       "            \"show\": true,\n",
       "            \"scale\": false,\n",
       "            \"nameLocation\": \"end\",\n",
       "            \"nameGap\": 15,\n",
       "            \"gridIndex\": 0,\n",
       "            \"inverse\": false,\n",
       "            \"offset\": 0,\n",
       "            \"splitNumber\": 5,\n",
       "            \"minInterval\": 0,\n",
       "            \"splitLine\": {\n",
       "                \"show\": false,\n",
       "                \"lineStyle\": {\n",
       "                    \"show\": true,\n",
       "                    \"width\": 1,\n",
       "                    \"opacity\": 1,\n",
       "                    \"curveness\": 0,\n",
       "                    \"type\": \"solid\"\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    ]\n",
       "};\n",
       "        chart_8c6f387ca5e14c4f9965a71fe6576318.setOption(option_8c6f387ca5e14c4f9965a71fe6576318);\n",
       "    </script>\n",
       "</body>\n",
       "</html>\n"
      ],
      "text/plain": [
       "<pyecharts.render.display.HTML at 0x12361b80>"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "line2=Line(figsize)\n",
    "line2.add_xaxis(X).add_yaxis(\"线1\",Y).add_yaxis(\"线2\",Z)\n",
    "line2.render_notebook()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5.4.3  基于数据框的绘图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>学号</th>\n",
       "      <th>性别</th>\n",
       "      <th>身高</th>\n",
       "      <th>体重</th>\n",
       "      <th>支出</th>\n",
       "      <th>开设</th>\n",
       "      <th>课程</th>\n",
       "      <th>软件</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1510248008</td>\n",
       "      <td>女</td>\n",
       "      <td>167</td>\n",
       "      <td>71</td>\n",
       "      <td>46.0</td>\n",
       "      <td>不清楚</td>\n",
       "      <td>都未学过</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1510229019</td>\n",
       "      <td>男</td>\n",
       "      <td>171</td>\n",
       "      <td>68</td>\n",
       "      <td>10.4</td>\n",
       "      <td>有必要</td>\n",
       "      <td>概率统计</td>\n",
       "      <td>Matlab</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1512108019</td>\n",
       "      <td>女</td>\n",
       "      <td>175</td>\n",
       "      <td>73</td>\n",
       "      <td>21.0</td>\n",
       "      <td>有必要</td>\n",
       "      <td>统计方法</td>\n",
       "      <td>SPSS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1512332010</td>\n",
       "      <td>男</td>\n",
       "      <td>169</td>\n",
       "      <td>74</td>\n",
       "      <td>4.9</td>\n",
       "      <td>有必要</td>\n",
       "      <td>编程技术</td>\n",
       "      <td>Excel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1512331015</td>\n",
       "      <td>男</td>\n",
       "      <td>154</td>\n",
       "      <td>55</td>\n",
       "      <td>25.9</td>\n",
       "      <td>有必要</td>\n",
       "      <td>都学习过</td>\n",
       "      <td>Python</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           学号 性别   身高  体重    支出   开设    课程      软件\n",
       "0  1510248008  女  167  71  46.0  不清楚  都未学过      No\n",
       "1  1510229019  男  171  68  10.4  有必要  概率统计  Matlab\n",
       "2  1512108019  女  175  73  21.0  有必要  统计方法    SPSS\n",
       "3  1512332010  男  169  74   4.9  有必要  编程技术   Excel\n",
       "4  1512331015  男  154  55  25.9  有必要  都学习过  Python"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "BS=pd.read_excel('DaPy_data.xlsx','BSdata');  #继续使用BSdata数据\n",
    "BS.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 5.4.3.1 原始数据散点图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<!DOCTYPE html>\n",
       "<html>\n",
       "<head>\n",
       "    <meta charset=\"UTF-8\">\n",
       "</head>\n",
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       "        <div id=\"86edf0a706084951bb61ce887c3bb2b7\" class=\"chart-container\" style=\"width:560px; height:380px;\"></div>\n",
       "    <script>\n",
       "        var chart_86edf0a706084951bb61ce887c3bb2b7 = echarts.init(\n",
       "            document.getElementById('86edf0a706084951bb61ce887c3bb2b7'), 'white', {renderer: 'canvas'});\n",
       "        var option_86edf0a706084951bb61ce887c3bb2b7 = {\n",
       "    \"backgroundColor\": \"white\",\n",
       "    \"animation\": true,\n",
       "    \"animationThreshold\": 2000,\n",
       "    \"animationDuration\": 1000,\n",
       "    \"animationEasing\": \"cubicOut\",\n",
       "    \"animationDelay\": 0,\n",
       "    \"animationDurationUpdate\": 300,\n",
       "    \"animationEasingUpdate\": \"cubicOut\",\n",
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       "            ],\n",
       "            \"label\": {\n",
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       "                \"margin\": 8\n",
       "            }\n",
       "        }\n",
       "    ],\n",
       "    \"legend\": [\n",
       "        {\n",
       "            \"data\": [\n",
       "                \"\"\n",
       "            ],\n",
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       "                \"\": true\n",
       "            }\n",
       "        }\n",
       "    ],\n",
       "    \"tooltip\": {\n",
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       "        \"trigger\": \"item\",\n",
       "        \"triggerOn\": \"mousemove|click\",\n",
       "        \"axisPointer\": {\n",
       "            \"type\": \"line\"\n",
       "        },\n",
       "        \"showContent\": true,\n",
       "        \"alwaysShowContent\": false,\n",
       "        \"showDelay\": 0,\n",
       "        \"hideDelay\": 100,\n",
       "        \"textStyle\": {\n",
       "            \"fontSize\": 14\n",
       "        },\n",
       "        \"borderWidth\": 0,\n",
       "        \"padding\": 5\n",
       "    },\n",
       "    \"xAxis\": [\n",
       "        {\n",
       "            \"show\": true,\n",
       "            \"scale\": false,\n",
       "            \"nameLocation\": \"end\",\n",
       "            \"nameGap\": 15,\n",
       "            \"gridIndex\": 0,\n",
       "            \"inverse\": false,\n",
       "            \"offset\": 0,\n",
       "            \"splitNumber\": 5,\n",
       "            \"minInterval\": 0,\n",
       "            \"splitLine\": {\n",
       "                \"show\": false,\n",
       "                \"lineStyle\": {\n",
       "                    \"show\": true,\n",
       "                    \"width\": 1,\n",
       "                    \"opacity\": 1,\n",
       "                    \"curveness\": 0,\n",
       "                    \"type\": \"solid\"\n",
       "                }\n",
       "            },\n",
       "            \"data\": null\n",
       "        }\n",
       "    ],\n",
       "    \"yAxis\": [\n",
       "        {\n",
       "            \"show\": true,\n",
       "            \"scale\": false,\n",
       "            \"nameLocation\": \"end\",\n",
       "            \"nameGap\": 15,\n",
       "            \"gridIndex\": 0,\n",
       "            \"inverse\": false,\n",
       "            \"offset\": 0,\n",
       "            \"splitNumber\": 5,\n",
       "            \"minInterval\": 0,\n",
       "            \"splitLine\": {\n",
       "                \"show\": false,\n",
       "                \"lineStyle\": {\n",
       "                    \"show\": true,\n",
       "                    \"width\": 1,\n",
       "                    \"opacity\": 1,\n",
       "                    \"curveness\": 0,\n",
       "                    \"type\": \"solid\"\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    ]\n",
       "};\n",
       "        chart_86edf0a706084951bb61ce887c3bb2b7.setOption(option_86edf0a706084951bb61ce887c3bb2b7);\n",
       "    </script>\n",
       "</body>\n",
       "</html>\n"
      ],
      "text/plain": [
       "<pyecharts.render.display.HTML at 0x127a0ee0>"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from pyecharts.charts import Scatter\n",
    "scatter1=Scatter(figsize)\n",
    "scatter1.add_xaxis(BS.身高).add_yaxis(\"\",BS.体重)\n",
    "scatter1.render_notebook()    #默认散点图的x轴和y轴从0开始"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<!DOCTYPE html>\n",
       "<html>\n",
       "<head>\n",
       "    <meta charset=\"UTF-8\">\n",
       "</head>\n",
       "<body>\n",
       "        <div id=\"6ae697b9b4a743b2b581ecb436c197cf\" class=\"chart-container\" style=\"width:560px; height:380px;\"></div>\n",
       "    <script>\n",
       "        var chart_6ae697b9b4a743b2b581ecb436c197cf = echarts.init(\n",
       "            document.getElementById('6ae697b9b4a743b2b581ecb436c197cf'), 'white', {renderer: 'canvas'});\n",
       "        var option_6ae697b9b4a743b2b581ecb436c197cf = {\n",
       "    \"backgroundColor\": \"white\",\n",
       "    \"animation\": true,\n",
       "    \"animationThreshold\": 2000,\n",
       "    \"animationDuration\": 1000,\n",
       "    \"animationEasing\": \"cubicOut\",\n",
       "    \"animationDelay\": 0,\n",
       "    \"animationDurationUpdate\": 300,\n",
       "    \"animationEasingUpdate\": \"cubicOut\",\n",
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       "                ]\n",
       "            ],\n",
       "            \"label\": {\n",
       "                \"show\": false,\n",
       "                \"position\": \"top\",\n",
       "                \"margin\": 8\n",
       "            }\n",
       "        }\n",
       "    ],\n",
       "    \"legend\": [\n",
       "        {\n",
       "            \"data\": [\n",
       "                \"\\u6563\\u70b9\\u56fe\"\n",
       "            ],\n",
       "            \"selected\": {\n",
       "                \"\\u6563\\u70b9\\u56fe\": true\n",
       "            },\n",
       "            \"show\": true,\n",
       "            \"padding\": 5,\n",
       "            \"itemGap\": 10,\n",
       "            \"itemWidth\": 25,\n",
       "            \"itemHeight\": 14\n",
       "        }\n",
       "    ],\n",
       "    \"tooltip\": {\n",
       "        \"show\": true,\n",
       "        \"trigger\": \"item\",\n",
       "        \"triggerOn\": \"mousemove|click\",\n",
       "        \"axisPointer\": {\n",
       "            \"type\": \"line\"\n",
       "        },\n",
       "        \"showContent\": true,\n",
       "        \"alwaysShowContent\": false,\n",
       "        \"showDelay\": 0,\n",
       "        \"hideDelay\": 100,\n",
       "        \"textStyle\": {\n",
       "            \"fontSize\": 14\n",
       "        },\n",
       "        \"borderWidth\": 0,\n",
       "        \"padding\": 5\n",
       "    },\n",
       "    \"xAxis\": [\n",
       "        {\n",
       "            \"show\": true,\n",
       "            \"scale\": false,\n",
       "            \"nameLocation\": \"end\",\n",
       "            \"nameGap\": 15,\n",
       "            \"gridIndex\": 0,\n",
       "            \"inverse\": false,\n",
       "            \"offset\": 0,\n",
       "            \"splitNumber\": 5,\n",
       "            \"min\": 150,\n",
       "            \"minInterval\": 0,\n",
       "            \"splitLine\": {\n",
       "                \"show\": false,\n",
       "                \"lineStyle\": {\n",
       "                    \"show\": true,\n",
       "                    \"width\": 1,\n",
       "                    \"opacity\": 1,\n",
       "                    \"curveness\": 0,\n",
       "                    \"type\": \"solid\"\n",
       "                }\n",
       "            },\n",
       "            \"data\": null\n",
       "        }\n",
       "    ],\n",
       "    \"yAxis\": [\n",
       "        {\n",
       "            \"show\": true,\n",
       "            \"scale\": false,\n",
       "            \"nameLocation\": \"end\",\n",
       "            \"nameGap\": 15,\n",
       "            \"gridIndex\": 0,\n",
       "            \"inverse\": false,\n",
       "            \"offset\": 0,\n",
       "            \"splitNumber\": 5,\n",
       "            \"min\": 40,\n",
       "            \"minInterval\": 0,\n",
       "            \"splitLine\": {\n",
       "                \"show\": false,\n",
       "                \"lineStyle\": {\n",
       "                    \"show\": true,\n",
       "                    \"width\": 1,\n",
       "                    \"opacity\": 1,\n",
       "                    \"curveness\": 0,\n",
       "                    \"type\": \"solid\"\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    ],\n",
       "    \"title\": [\n",
       "        {\n",
       "            \"padding\": 5,\n",
       "            \"itemGap\": 10\n",
       "        }\n",
       "    ]\n",
       "};\n",
       "        chart_6ae697b9b4a743b2b581ecb436c197cf.setOption(option_6ae697b9b4a743b2b581ecb436c197cf);\n",
       "    </script>\n",
       "</body>\n",
       "</html>\n"
      ],
      "text/plain": [
       "<pyecharts.render.display.HTML at 0x11115fa0>"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#修改x轴和y轴的刻度\n",
    "scatter2=(Scatter(figsize)\n",
    "   .add_xaxis(BS.身高) \n",
    "   .add_yaxis(\"散点图\",BS.体重,label_opts=opts.LabelOpts(is_show=False))  \n",
    "   .set_global_opts(\n",
    "       xaxis_opts=opts.AxisOpts(min_=150), #x轴最小150\n",
    "       yaxis_opts=opts.AxisOpts(min_=40)   #y轴最小40 \n",
    "   )\n",
    ")\n",
    "scatter2.render_notebook()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5.4.3.2 统计数据的条图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>学号</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>性别</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>女</th>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>男</th>\n",
       "      <td>27</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    学号\n",
       "性别    \n",
       "女   25\n",
       "男   27"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#基本的pyecharts绘图是基于列表数据的, 通常需将数据框转换成列表\n",
    "pt1=BS.pivot_table(index=['性别'],values=['学号'],aggfunc=len); pt1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<!DOCTYPE html>\n",
       "<html>\n",
       "<head>\n",
       "    <meta charset=\"UTF-8\">\n",
       "</head>\n",
       "<body>\n",
       "        <div id=\"b37b1ceb88514edd96a5d766a7589bcb\" class=\"chart-container\" style=\"width:560px; height:380px;\"></div>\n",
       "    <script>\n",
       "        var chart_b37b1ceb88514edd96a5d766a7589bcb = echarts.init(\n",
       "            document.getElementById('b37b1ceb88514edd96a5d766a7589bcb'), 'white', {renderer: 'canvas'});\n",
       "        var option_b37b1ceb88514edd96a5d766a7589bcb = {\n",
       "    \"backgroundColor\": \"white\",\n",
       "    \"animation\": true,\n",
       "    \"animationThreshold\": 2000,\n",
       "    \"animationDuration\": 1000,\n",
       "    \"animationEasing\": \"cubicOut\",\n",
       "    \"animationDelay\": 0,\n",
       "    \"animationDurationUpdate\": 300,\n",
       "    \"animationEasingUpdate\": \"cubicOut\",\n",
       "    \"animationDelayUpdate\": 0,\n",
       "    \"color\": [\n",
       "        \"#c23531\",\n",
       "        \"#2f4554\",\n",
       "        \"#61a0a8\",\n",
       "        \"#d48265\",\n",
       "        \"#749f83\",\n",
       "        \"#ca8622\",\n",
       "        \"#bda29a\",\n",
       "        \"#6e7074\",\n",
       "        \"#546570\",\n",
       "        \"#c4ccd3\",\n",
       "        \"#f05b72\",\n",
       "        \"#ef5b9c\",\n",
       "        \"#f47920\",\n",
       "        \"#905a3d\",\n",
       "        \"#fab27b\",\n",
       "        \"#2a5caa\",\n",
       "        \"#444693\",\n",
       "        \"#726930\",\n",
       "        \"#b2d235\",\n",
       "        \"#6d8346\",\n",
       "        \"#ac6767\",\n",
       "        \"#1d953f\",\n",
       "        \"#6950a1\",\n",
       "        \"#918597\"\n",
       "    ],\n",
       "    \"series\": [\n",
       "        {\n",
       "            \"type\": \"bar\",\n",
       "            \"name\": \"\\u6027\\u522b\\u7edf\\u8ba1\\u56fe\",\n",
       "            \"legendHoverLink\": true,\n",
       "            \"data\": [\n",
       "                25,\n",
       "                27\n",
       "            ],\n",
       "            \"showBackground\": false,\n",
       "            \"barMinHeight\": 0,\n",
       "            \"barCategoryGap\": \"20%\",\n",
       "            \"barGap\": \"30%\",\n",
       "            \"large\": false,\n",
       "            \"largeThreshold\": 400,\n",
       "            \"seriesLayoutBy\": \"column\",\n",
       "            \"datasetIndex\": 0,\n",
       "            \"clip\": true,\n",
       "            \"zlevel\": 0,\n",
       "            \"z\": 2,\n",
       "            \"label\": {\n",
       "                \"show\": true,\n",
       "                \"position\": \"top\",\n",
       "                \"margin\": 8\n",
       "            }\n",
       "        }\n",
       "    ],\n",
       "    \"legend\": [\n",
       "        {\n",
       "            \"data\": [\n",
       "                \"\\u6027\\u522b\\u7edf\\u8ba1\\u56fe\"\n",
       "            ],\n",
       "            \"selected\": {\n",
       "                \"\\u6027\\u522b\\u7edf\\u8ba1\\u56fe\": true\n",
       "            }\n",
       "        }\n",
       "    ],\n",
       "    \"tooltip\": {\n",
       "        \"show\": true,\n",
       "        \"trigger\": \"item\",\n",
       "        \"triggerOn\": \"mousemove|click\",\n",
       "        \"axisPointer\": {\n",
       "            \"type\": \"line\"\n",
       "        },\n",
       "        \"showContent\": true,\n",
       "        \"alwaysShowContent\": false,\n",
       "        \"showDelay\": 0,\n",
       "        \"hideDelay\": 100,\n",
       "        \"textStyle\": {\n",
       "            \"fontSize\": 14\n",
       "        },\n",
       "        \"borderWidth\": 0,\n",
       "        \"padding\": 5\n",
       "    },\n",
       "    \"xAxis\": [\n",
       "        {\n",
       "            \"show\": true,\n",
       "            \"scale\": false,\n",
       "            \"nameLocation\": \"end\",\n",
       "            \"nameGap\": 15,\n",
       "            \"gridIndex\": 0,\n",
       "            \"inverse\": false,\n",
       "            \"offset\": 0,\n",
       "            \"splitNumber\": 5,\n",
       "            \"minInterval\": 0,\n",
       "            \"splitLine\": {\n",
       "                \"show\": false,\n",
       "                \"lineStyle\": {\n",
       "                    \"show\": true,\n",
       "                    \"width\": 1,\n",
       "                    \"opacity\": 1,\n",
       "                    \"curveness\": 0,\n",
       "                    \"type\": \"solid\"\n",
       "                }\n",
       "            },\n",
       "            \"data\": [\n",
       "                \"\\u5973\",\n",
       "                \"\\u7537\"\n",
       "            ]\n",
       "        }\n",
       "    ],\n",
       "    \"yAxis\": [\n",
       "        {\n",
       "            \"show\": true,\n",
       "            \"scale\": false,\n",
       "            \"nameLocation\": \"end\",\n",
       "            \"nameGap\": 15,\n",
       "            \"gridIndex\": 0,\n",
       "            \"inverse\": false,\n",
       "            \"offset\": 0,\n",
       "            \"splitNumber\": 5,\n",
       "            \"minInterval\": 0,\n",
       "            \"splitLine\": {\n",
       "                \"show\": false,\n",
       "                \"lineStyle\": {\n",
       "                    \"show\": true,\n",
       "                    \"width\": 1,\n",
       "                    \"opacity\": 1,\n",
       "                    \"curveness\": 0,\n",
       "                    \"type\": \"solid\"\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    ]\n",
       "};\n",
       "        chart_b37b1ceb88514edd96a5d766a7589bcb.setOption(option_b37b1ceb88514edd96a5d766a7589bcb);\n",
       "    </script>\n",
       "</body>\n",
       "</html>\n"
      ],
      "text/plain": [
       "<pyecharts.render.display.HTML at 0x12784c70>"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from pyecharts.charts import Bar  \n",
    "(Bar(figsize)\n",
    "     .add_xaxis(list(pt1.index))\n",
    "     .add_yaxis(\"性别统计图\",list(pt1.学号))\n",
    "     .render_notebook()\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr:last-of-type th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"2\" halign=\"left\">学号</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>性别</th>\n",
       "      <th>女</th>\n",
       "      <th>男</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>开设</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>不必要</th>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>不清楚</th>\n",
       "      <td>9</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>有必要</th>\n",
       "      <td>10</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     学号    \n",
       "性别    女   男\n",
       "开设         \n",
       "不必要   6   5\n",
       "不清楚   9   3\n",
       "有必要  10  19"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pt2=BS.pivot_table(['学号'],['开设'],['性别'],aggfunc=len); pt2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<!DOCTYPE html>\n",
       "<html>\n",
       "<head>\n",
       "    <meta charset=\"UTF-8\">\n",
       "</head>\n",
       "<body>\n",
       "        <div id=\"faed7b7844bd4a33a2725666a3387566\" class=\"chart-container\" style=\"width:560px; height:380px;\"></div>\n",
       "    <script>\n",
       "        var chart_faed7b7844bd4a33a2725666a3387566 = echarts.init(\n",
       "            document.getElementById('faed7b7844bd4a33a2725666a3387566'), 'white', {renderer: 'canvas'});\n",
       "        var option_faed7b7844bd4a33a2725666a3387566 = {\n",
       "    \"backgroundColor\": \"white\",\n",
       "    \"animation\": true,\n",
       "    \"animationThreshold\": 2000,\n",
       "    \"animationDuration\": 1000,\n",
       "    \"animationEasing\": \"cubicOut\",\n",
       "    \"animationDelay\": 0,\n",
       "    \"animationDurationUpdate\": 300,\n",
       "    \"animationEasingUpdate\": \"cubicOut\",\n",
       "    \"animationDelayUpdate\": 0,\n",
       "    \"color\": [\n",
       "        \"#c23531\",\n",
       "        \"#2f4554\",\n",
       "        \"#61a0a8\",\n",
       "        \"#d48265\",\n",
       "        \"#749f83\",\n",
       "        \"#ca8622\",\n",
       "        \"#bda29a\",\n",
       "        \"#6e7074\",\n",
       "        \"#546570\",\n",
       "        \"#c4ccd3\",\n",
       "        \"#f05b72\",\n",
       "        \"#ef5b9c\",\n",
       "        \"#f47920\",\n",
       "        \"#905a3d\",\n",
       "        \"#fab27b\",\n",
       "        \"#2a5caa\",\n",
       "        \"#444693\",\n",
       "        \"#726930\",\n",
       "        \"#b2d235\",\n",
       "        \"#6d8346\",\n",
       "        \"#ac6767\",\n",
       "        \"#1d953f\",\n",
       "        \"#6950a1\",\n",
       "        \"#918597\"\n",
       "    ],\n",
       "    \"series\": [\n",
       "        {\n",
       "            \"type\": \"bar\",\n",
       "            \"name\": \"\\u5973\",\n",
       "            \"legendHoverLink\": true,\n",
       "            \"data\": [\n",
       "                6,\n",
       "                9,\n",
       "                10\n",
       "            ],\n",
       "            \"showBackground\": false,\n",
       "            \"barMinHeight\": 0,\n",
       "            \"barCategoryGap\": \"20%\",\n",
       "            \"barGap\": \"30%\",\n",
       "            \"large\": false,\n",
       "            \"largeThreshold\": 400,\n",
       "            \"seriesLayoutBy\": \"column\",\n",
       "            \"datasetIndex\": 0,\n",
       "            \"clip\": true,\n",
       "            \"zlevel\": 0,\n",
       "            \"z\": 2,\n",
       "            \"label\": {\n",
       "                \"show\": true,\n",
       "                \"position\": \"top\",\n",
       "                \"margin\": 8\n",
       "            }\n",
       "        },\n",
       "        {\n",
       "            \"type\": \"bar\",\n",
       "            \"name\": \"\\u7537\",\n",
       "            \"legendHoverLink\": true,\n",
       "            \"data\": [\n",
       "                5,\n",
       "                3,\n",
       "                19\n",
       "            ],\n",
       "            \"showBackground\": false,\n",
       "            \"barMinHeight\": 0,\n",
       "            \"barCategoryGap\": \"20%\",\n",
       "            \"barGap\": \"30%\",\n",
       "            \"large\": false,\n",
       "            \"largeThreshold\": 400,\n",
       "            \"seriesLayoutBy\": \"column\",\n",
       "            \"datasetIndex\": 0,\n",
       "            \"clip\": true,\n",
       "            \"zlevel\": 0,\n",
       "            \"z\": 2,\n",
       "            \"label\": {\n",
       "                \"show\": true,\n",
       "                \"position\": \"top\",\n",
       "                \"margin\": 8\n",
       "            }\n",
       "        }\n",
       "    ],\n",
       "    \"legend\": [\n",
       "        {\n",
       "            \"data\": [\n",
       "                \"\\u5973\",\n",
       "                \"\\u7537\"\n",
       "            ],\n",
       "            \"selected\": {\n",
       "                \"\\u5973\": true,\n",
       "                \"\\u7537\": true\n",
       "            }\n",
       "        }\n",
       "    ],\n",
       "    \"tooltip\": {\n",
       "        \"show\": true,\n",
       "        \"trigger\": \"item\",\n",
       "        \"triggerOn\": \"mousemove|click\",\n",
       "        \"axisPointer\": {\n",
       "            \"type\": \"line\"\n",
       "        },\n",
       "        \"showContent\": true,\n",
       "        \"alwaysShowContent\": false,\n",
       "        \"showDelay\": 0,\n",
       "        \"hideDelay\": 100,\n",
       "        \"textStyle\": {\n",
       "            \"fontSize\": 14\n",
       "        },\n",
       "        \"borderWidth\": 0,\n",
       "        \"padding\": 5\n",
       "    },\n",
       "    \"xAxis\": [\n",
       "        {\n",
       "            \"show\": true,\n",
       "            \"scale\": false,\n",
       "            \"nameLocation\": \"end\",\n",
       "            \"nameGap\": 15,\n",
       "            \"gridIndex\": 0,\n",
       "            \"inverse\": false,\n",
       "            \"offset\": 0,\n",
       "            \"splitNumber\": 5,\n",
       "            \"minInterval\": 0,\n",
       "            \"splitLine\": {\n",
       "                \"show\": false,\n",
       "                \"lineStyle\": {\n",
       "                    \"show\": true,\n",
       "                    \"width\": 1,\n",
       "                    \"opacity\": 1,\n",
       "                    \"curveness\": 0,\n",
       "                    \"type\": \"solid\"\n",
       "                }\n",
       "            },\n",
       "            \"data\": [\n",
       "                \"\\u4e0d\\u5fc5\\u8981\",\n",
       "                \"\\u4e0d\\u6e05\\u695a\",\n",
       "                \"\\u6709\\u5fc5\\u8981\"\n",
       "            ]\n",
       "        }\n",
       "    ],\n",
       "    \"yAxis\": [\n",
       "        {\n",
       "            \"show\": true,\n",
       "            \"scale\": false,\n",
       "            \"nameLocation\": \"end\",\n",
       "            \"nameGap\": 15,\n",
       "            \"gridIndex\": 0,\n",
       "            \"inverse\": false,\n",
       "            \"offset\": 0,\n",
       "            \"splitNumber\": 5,\n",
       "            \"minInterval\": 0,\n",
       "            \"splitLine\": {\n",
       "                \"show\": false,\n",
       "                \"lineStyle\": {\n",
       "                    \"show\": true,\n",
       "                    \"width\": 1,\n",
       "                    \"opacity\": 1,\n",
       "                    \"curveness\": 0,\n",
       "                    \"type\": \"solid\"\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    ]\n",
       "};\n",
       "        chart_faed7b7844bd4a33a2725666a3387566.setOption(option_faed7b7844bd4a33a2725666a3387566);\n",
       "    </script>\n",
       "</body>\n",
       "</html>\n"
      ],
      "text/plain": [
       "<pyecharts.render.display.HTML at 0x1082b7c0>"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(Bar(figsize)\n",
    "     .add_xaxis(list(pt2.index))\n",
    "     .add_yaxis(\"女\",list(pt2.学号.女))\n",
    "     .add_yaxis(\"男\",list(pt2.学号.男))\n",
    "     .render_notebook()\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr:last-of-type th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"2\" halign=\"left\">支出</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>开设</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>不必要</th>\n",
       "      <td>36.68</td>\n",
       "      <td>26.47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>不清楚</th>\n",
       "      <td>26.29</td>\n",
       "      <td>20.87</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>有必要</th>\n",
       "      <td>19.16</td>\n",
       "      <td>18.06</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        支出       \n",
       "      mean    std\n",
       "开设               \n",
       "不必要  36.68  26.47\n",
       "不清楚  26.29  20.87\n",
       "有必要  19.16  18.06"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import numpy as np\n",
    "pt3=BS.pivot_table([\"支出\"],['开设'],aggfunc={np.mean,np.std});\n",
    "pt3=pt3.round(2); pt3   #pt3['支出']['mean']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<!DOCTYPE html>\n",
       "<html>\n",
       "<head>\n",
       "    <meta charset=\"UTF-8\">\n",
       "</head>\n",
       "<body>\n",
       "        <div id=\"a966c56b878941919a521438de07c423\" class=\"chart-container\" style=\"width:560px; height:380px;\"></div>\n",
       "    <script>\n",
       "        var chart_a966c56b878941919a521438de07c423 = echarts.init(\n",
       "            document.getElementById('a966c56b878941919a521438de07c423'), 'white', {renderer: 'canvas'});\n",
       "        var option_a966c56b878941919a521438de07c423 = {\n",
       "    \"backgroundColor\": \"white\",\n",
       "    \"animation\": true,\n",
       "    \"animationThreshold\": 2000,\n",
       "    \"animationDuration\": 1000,\n",
       "    \"animationEasing\": \"cubicOut\",\n",
       "    \"animationDelay\": 0,\n",
       "    \"animationDurationUpdate\": 300,\n",
       "    \"animationEasingUpdate\": \"cubicOut\",\n",
       "    \"animationDelayUpdate\": 0,\n",
       "    \"color\": [\n",
       "        \"#c23531\",\n",
       "        \"#2f4554\",\n",
       "        \"#61a0a8\",\n",
       "        \"#d48265\",\n",
       "        \"#749f83\",\n",
       "        \"#ca8622\",\n",
       "        \"#bda29a\",\n",
       "        \"#6e7074\",\n",
       "        \"#546570\",\n",
       "        \"#c4ccd3\",\n",
       "        \"#f05b72\",\n",
       "        \"#ef5b9c\",\n",
       "        \"#f47920\",\n",
       "        \"#905a3d\",\n",
       "        \"#fab27b\",\n",
       "        \"#2a5caa\",\n",
       "        \"#444693\",\n",
       "        \"#726930\",\n",
       "        \"#b2d235\",\n",
       "        \"#6d8346\",\n",
       "        \"#ac6767\",\n",
       "        \"#1d953f\",\n",
       "        \"#6950a1\",\n",
       "        \"#918597\"\n",
       "    ],\n",
       "    \"series\": [\n",
       "        {\n",
       "            \"type\": \"bar\",\n",
       "            \"name\": \"\\u5747\\u503c\",\n",
       "            \"legendHoverLink\": true,\n",
       "            \"data\": [\n",
       "                36.68,\n",
       "                26.29,\n",
       "                19.16\n",
       "            ],\n",
       "            \"showBackground\": false,\n",
       "            \"barMinHeight\": 0,\n",
       "            \"barCategoryGap\": \"20%\",\n",
       "            \"barGap\": \"30%\",\n",
       "            \"large\": false,\n",
       "            \"largeThreshold\": 400,\n",
       "            \"seriesLayoutBy\": \"column\",\n",
       "            \"datasetIndex\": 0,\n",
       "            \"clip\": true,\n",
       "            \"zlevel\": 0,\n",
       "            \"z\": 2,\n",
       "            \"label\": {\n",
       "                \"show\": true,\n",
       "                \"position\": \"top\",\n",
       "                \"margin\": 8\n",
       "            }\n",
       "        },\n",
       "        {\n",
       "            \"type\": \"bar\",\n",
       "            \"name\": \"\\u6807\\u51c6\\u5dee\",\n",
       "            \"legendHoverLink\": true,\n",
       "            \"data\": [\n",
       "                26.47,\n",
       "                20.87,\n",
       "                18.06\n",
       "            ],\n",
       "            \"showBackground\": false,\n",
       "            \"barMinHeight\": 0,\n",
       "            \"barCategoryGap\": \"20%\",\n",
       "            \"barGap\": \"30%\",\n",
       "            \"large\": false,\n",
       "            \"largeThreshold\": 400,\n",
       "            \"seriesLayoutBy\": \"column\",\n",
       "            \"datasetIndex\": 0,\n",
       "            \"clip\": true,\n",
       "            \"zlevel\": 0,\n",
       "            \"z\": 2,\n",
       "            \"label\": {\n",
       "                \"show\": true,\n",
       "                \"position\": \"top\",\n",
       "                \"margin\": 8\n",
       "            }\n",
       "        }\n",
       "    ],\n",
       "    \"legend\": [\n",
       "        {\n",
       "            \"data\": [\n",
       "                \"\\u5747\\u503c\",\n",
       "                \"\\u6807\\u51c6\\u5dee\"\n",
       "            ],\n",
       "            \"selected\": {\n",
       "                \"\\u5747\\u503c\": true,\n",
       "                \"\\u6807\\u51c6\\u5dee\": true\n",
       "            }\n",
       "        }\n",
       "    ],\n",
       "    \"tooltip\": {\n",
       "        \"show\": true,\n",
       "        \"trigger\": \"item\",\n",
       "        \"triggerOn\": \"mousemove|click\",\n",
       "        \"axisPointer\": {\n",
       "            \"type\": \"line\"\n",
       "        },\n",
       "        \"showContent\": true,\n",
       "        \"alwaysShowContent\": false,\n",
       "        \"showDelay\": 0,\n",
       "        \"hideDelay\": 100,\n",
       "        \"textStyle\": {\n",
       "            \"fontSize\": 14\n",
       "        },\n",
       "        \"borderWidth\": 0,\n",
       "        \"padding\": 5\n",
       "    },\n",
       "    \"xAxis\": [\n",
       "        {\n",
       "            \"show\": true,\n",
       "            \"scale\": false,\n",
       "            \"nameLocation\": \"end\",\n",
       "            \"nameGap\": 15,\n",
       "            \"gridIndex\": 0,\n",
       "            \"inverse\": false,\n",
       "            \"offset\": 0,\n",
       "            \"splitNumber\": 5,\n",
       "            \"minInterval\": 0,\n",
       "            \"splitLine\": {\n",
       "                \"show\": false,\n",
       "                \"lineStyle\": {\n",
       "                    \"show\": true,\n",
       "                    \"width\": 1,\n",
       "                    \"opacity\": 1,\n",
       "                    \"curveness\": 0,\n",
       "                    \"type\": \"solid\"\n",
       "                }\n",
       "            },\n",
       "            \"data\": [\n",
       "                \"\\u4e0d\\u5fc5\\u8981\",\n",
       "                \"\\u4e0d\\u6e05\\u695a\",\n",
       "                \"\\u6709\\u5fc5\\u8981\"\n",
       "            ]\n",
       "        }\n",
       "    ],\n",
       "    \"yAxis\": [\n",
       "        {\n",
       "            \"show\": true,\n",
       "            \"scale\": false,\n",
       "            \"nameLocation\": \"end\",\n",
       "            \"nameGap\": 15,\n",
       "            \"gridIndex\": 0,\n",
       "            \"inverse\": false,\n",
       "            \"offset\": 0,\n",
       "            \"splitNumber\": 5,\n",
       "            \"minInterval\": 0,\n",
       "            \"splitLine\": {\n",
       "                \"show\": false,\n",
       "                \"lineStyle\": {\n",
       "                    \"show\": true,\n",
       "                    \"width\": 1,\n",
       "                    \"opacity\": 1,\n",
       "                    \"curveness\": 0,\n",
       "                    \"type\": \"solid\"\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    ]\n",
       "};\n",
       "        chart_a966c56b878941919a521438de07c423.setOption(option_a966c56b878941919a521438de07c423);\n",
       "    </script>\n",
       "</body>\n",
       "</html>\n"
      ],
      "text/plain": [
       "<pyecharts.render.display.HTML at 0x127f0b50>"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(Bar(figsize)\n",
    "      .add_xaxis(list(pt3.index))\n",
    "      .add_yaxis(\"均值\",list(pt3['支出']['mean']))  #list(pt3.iloc[:,0])\n",
    "      .add_yaxis(\"标准差\",list(pt3['支出']['std']))\n",
    "      .render_notebook()\n",
    ")"
   ]
  }
 ],
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   "language": "python",
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